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0 -11.25 TD 0.146 Tc 1.3331 Tw (find inconspicuous ways to achieve the direction. All of ) Tj
T* 0.1315 Tc 0.431 Tw (this direction integration must be done within the real) Tj
219 0 TD -0.2467 Tc 0 Tw (-) Tj
3 0 TD -0.2089 Tc 0.0214 Tw (time ) Tj
-222 -11.25 TD 0.1734 Tc 3.3891 Tw (constraints of the environment) Tj
134.25 0 TD 0.216 Tc 2.7465 Tw ( in which these agents ) Tj
-134.25 -11.25 TD 0.105 Tc -0.2925 Tw (typically operate ) Tj
69 0 TD -0.1794 Tc -0.0081 Tw (\(Laird et al 2002\)) Tj
65.25 0 TD -0.1875 Tc 0 Tw (.) Tj
2.25 0 TD 0 Tc -0.1875 Tw ( ) Tj
-136.5 -11.25 TD ( ) Tj
9.75 0 TD 0.1449 Tc 0.9176 Tw (In terms of performance, the agent\222s behavior needs to ) Tj
-9.75 -11.25 TD 0.0994 Tc 0.6131 Tw (achieve a competent level of performance on par with that ) Tj
0 -11.25 TD 0.1943 Tc 0.2932 Tw (of the author\222s envisioned character. To do this, the agent ) Tj
T* 0.4581 Tc 0 Tw (shou) Tj
20.25 0 TD 0.1637 Tc 0.1488 Tw (ld pursue goals and find methods to achieve them. ) Tj
207.75 0 TD /F2 9.75 Tf
0.102 Tc 0.4605 Tw (To ) Tj
-228 -11.25 TD 0.2678 Tc 0.4447 Tw (the degree defined by the author) Tj
136.5 0 TD /F1 9.75 Tf
0.2237 Tc 0.3388 Tw (, the agent\222s goal should ) Tj
-136.5 -11.25 TD 0.205 Tc 1.1075 Tw (be evident, and its action should appear to contribute to ) Tj
0 -11.25 TD 0.3086 Tc 1.3789 Tw (those goals ) Tj
54.75 0 TD 0.0366 Tc 2.7759 Tw (\(Sengers 1998b\)) Tj
66.75 0 TD 0.1591 Tc 1.5819 Tw (. Moreover, to do this in a ) Tj
-121.5 -11.25 TD 0.1024 Tc 2.7101 Tw (believable fash) Tj
63 0 TD 0.2238 Tc 1.8387 Tw (ion, this behavior should be based on a ) Tj
-63 -11.25 TD 0.0083 Tc 3.9292 Tw (model of limited character perception with realistically) Tj
0 Tc 0.5625 Tw ( ) Tj
0 -11.25 TD 0.0994 Tc 5.7131 Tw (embodied effectors) Tj
0 Tc 0.5625 Tw ( ) Tj
90.75 0 TD -0.1015 Tc 5.1641 Tw (\(Freed et al 2000\)) Tj
83.25 0 TD -0.0451 Tc 5.1076 Tw (. Of particular) Tj
0 Tc -0.1875 Tw ( ) Tj
-174 -11.25 TD 0.1089 Tc 1.9536 Tw (importance to believably integrating direction, the agent ) Tj
0 -11.25 TD 0.176 Tc 0.1365 Tw (should not schizophrenically sw) Tj
130.5 0 TD 0.112 Tc -0.2995 Tw (itch between goals. Rather, ) Tj
-130.5 -11.25 TD 0.129 Tc 2.6835 Tw (all of its behavior should be fairly continuous and fit ) Tj
0 -11.25 TD 0.187 Tc 0.3755 Tw (together in a coherent fashion ) Tj
126 0 TD 0.0221 Tc 0.5404 Tw (\(Sengers 1998a\)) Tj
63.75 0 TD 0.0487 Tc 0.5138 Tw (. In the next ) Tj
-189.75 -11.25 TD 0.0864 Tc 1.9761 Tw (section, we will discuss different forms of coherency in ) Tj
0 -11.25 TD 0.0416 Tc -0.2291 Tw (greater detail.) Tj
54 0 TD 0 Tc -0.1875 Tw ( ) Tj
-54 -11.25 TD ( ) Tj
9.75 0 TD 0.0252 Tc 5.7873 Tw (The individualization) Tj
90 0 TD 0.1459 Tc 5.6666 Tw ( criteria establish the agent\222s) Tj
0 Tc 0.5625 Tw ( ) Tj
-99.75 -11.25 TD 0.2028 Tc 7.7347 Tw (dramatic character. The agent should possess a) Tj
0 Tc -0.1875 Tw ( ) Tj
0 -11.25 TD 0.1376 Tc 3.7999 Tw (distinguishable personality that manifests itself in the) Tj
0 Tc -0.1875 Tw ( ) Tj
T* 0.2076 Tc 0.2185 Tw (agent\222s actions. In some cases, social roles can be used to ) Tj
T* 0.0769 Tc 0.7356 Tw (prime the user\222s expectations and more clearly define who ) Tj
T* 0.3322 Tc 0 Tw (th) Tj
8.25 0 TD 0.2249 Tc 0.8376 Tw (e agent is ) Tj
45 0 TD 0.023 Tc 0 Tw (\(Hayes) Tj
28.5 0 TD -0.2467 Tc (-) Tj
3 0 TD 0.0024 Tc 0.5601 Tw (Roth and Rousseau 1997; Reilly 1994; ) Tj
-84.75 -11.25 TD 0.042 Tc 5.7705 Tw (Reilly 1996; Rousseau and Hayes) Tj
156.75 0 TD -0.2467 Tc 0 Tw (-) Tj
3 0 TD -0.207 Tc 5.6445 Tw (Roth 1996, 1997\)) Tj
76.5 0 TD -0.1875 Tc 0 Tw (. ) Tj
-236.25 -11.25 TD 0.1218 Tc 1.9407 Tw (Furthermore, the agent should have either an emotional ) Tj
0 -11.25 TD 0.0732 Tc 1.2393 Tw (model or a method to approximate emotionally consistent ) Tj
T* 0.1418 Tc -0.3293 Tw (behavior ) Tj
38.25 0 TD 0.0127 Tc 0.0998 Tw (\(Bates et al 1992a, b; Hayes) Tj
111 0 TD -0.2467 Tc 0 Tw (-) Tj
3 0 TD 0.0246 Tc -0.0246 Tw (Roth and Doyle 1998; ) Tj
-152.25 -11.25 TD -0.1293 Tc 4.1418 Tw (Reilly and Bates 1992; Reilly 1996\)) Tj
156.75 0 TD -0.0416 Tc 3.6041 Tw (. Finally, our ideal) Tj
0 Tc -0.1875 Tw ( ) Tj
-156.75 -11.25 TD 0.1765 Tc 1.0527 Tw (believable agent should have memory of both the events ) Tj
0 -11.25 TD 0.1554 Tc 0.4071 Tw (that occur in the simulated environment and the purported ) Tj
T* 0.273 Tc 0 Tw (back) Tj
18.75 0 TD -0.2467 Tc (-) Tj
3 0 TD 0.1651 Tc -0.3526 Tw (story of the character. ) Tj
90 0 TD 0 Tc -0.1875 Tw ( ) Tj
213.75 406.5 TD /F0 12 Tf
-0.414 Tc 0 Tw (Dire) Tj
22.5 0 TD -0.2054 Tc 0.2054 Tw (cted Goal Conflicts) Tj
95.25 0 TD 0 Tc 0 Tw ( ) Tj
-177.75 -18 TD /F1 9.75 Tf
0.1061 Tc 2.0314 Tw (Assuming that direction comes in the form of a known ) Tj
0 -11.25 TD 0.1718 Tc 0.1407 Tw (agent goal, we can use our design criteria to generate a set ) Tj
T* 0.1509 Tc -0.3384 Tw (of possible conflicts that a directed goal can introduce. ) Tj
221.25 0 TD 0 Tc -0.1875 Tw ( ) Tj
-221.25 -11.25 TD 0.0978 Tc -0.2853 Tw (We will define two categories of conflicts:) Tj
167.25 0 TD 0 Tc -0.1875 Tw ( ) Tj
-157.5 -17.25 TD /F0 9.75 Tf
-0.0086 Tc 4.3211 Tw (Goal Consistency) Tj
75.75 0 TD /F1 9.75 Tf
-0.4605 Tc 4.773 Tw (: ) Tj
4.671 Tc 0 Tw (c) Tj
13.5 0 TD 0.082 Tc 3.7305 Tw (ompatibility between goals or) Tj
0 Tc -0.1875 Tw ( ) Tj
-89.25 -11.25 TD 0.2042 Tc -0.3917 Tw (among components of goals.) Tj
115.5 0 TD 0 Tc -0.1875 Tw ( ) Tj
-115.5 -17.25 TD /F0 9.75 Tf
-0.0957 Tc 2.9082 Tw (Goal Coherency) Tj
68.25 0 TD /F1 9.75 Tf
0.117 Tc 2.0392 Tw (: the quality of having a clear and ) Tj
-68.25 -11.25 TD 0.1606 Tc 10.1519 Tw (logical structure between goals and being) Tj
0 Tc 0.5625 Tw ( ) Tj
0 -11.25 TD 0.2006 Tc -0.3881 Tw (understandable in and of themselves.) Tj
149.25 0 TD 0 Tc -0.1875 Tw ( ) Tj
-159 -13.5 TD /F1 12 Tf
0 Tw ( ) Tj
0 -12 TD /F1 9.75 Tf
-0.1875 Tw ( ) Tj
9.75 0 TD 0.0958 Tc 6.7881 Tw (We can split our definition of believable goal) Tj
0 Tc -0.1875 Tw ( ) Tj
-9.75 -11.25 TD 0.2339 Tc 4.0786 Tw (consistency into two) Tj
0 Tc 0.5625 Tw ( ) Tj
99.75 0 TD 0.2169 Tc 3.8456 Tw (cases: specific consistency and) Tj
0 Tc 0.5625 Tw ( ) Tj
-99.75 -11.25 TD 0.1751 Tc 2.8874 Tw (general consistency. We define) Tj
0 Tc -0.1875 Tw ( ) Tj
141 0 TD /F2 9.75 Tf
0.1719 Tc 2.6406 Tw (specific consistency) Tj
83.25 0 TD /F1 9.75 Tf
0.4391 Tc 1.2484 Tw ( as ) Tj
-224.25 -11.25 TD 0.1155 Tc -0.1155 Tw (complete compatibility between the conditions of two goals ) Tj
0 -11.25 TD 0.1653 Tc -0.1861 Tw (or the components of two goals. Specific inconsistency can ) Tj
T* 0.182 Tc 1.9876 Tw (occur because either \(a\) the goal conditions themse) Tj
222 0 TD 0.1982 Tc 0.3643 Tw (lves ) Tj
-222 -11.25 TD 0.0267 Tc 0.5358 Tw (conflict ) Tj
33.75 0 TD 0.375 Tc 0 Tw (\226) Tj
5.25 0 TD 0.1469 Tc 0.6656 Tw ( both goals cannot coexist at the same time ) Tj
183 0 TD 0.375 Tc 0 Tw (\226) Tj
5.25 0 TD 0.0641 Tc 0.1234 Tw ( or ) Tj
-227.25 -11.25 TD 0.131 Tc 0.0224 Tw (\(b\) there are potential threats in the achievement of the two ) Tj
0 -11.25 TD 0.2335 Tc 0.3289 Tw (goals ) Tj
27.75 0 TD -0.2467 Tc 0 Tw (--) Tj
6 0 TD 0.1776 Tc 2.4099 Tw ( the precondition of some step of one goal is ) Tj
-33.75 -11.25 TD 0.1669 Tc 5.1769 Tw (potentially clobbered by a step of the other goal.) Tj
0 Tc -0.1875 Tw ( ) Tj
0 -11.25 TD 0.0631 Tc 1.9994 Tw (Obviously, this is comple) Tj
108 0 TD 0.198 Tc 1.1145 Tw (tely analogous to conflicts and ) Tj
-108 -11.25 TD 0.095 Tc -0.2825 Tw (threats in planning literature. ) Tj
117 0 TD 0 Tc -0.1875 Tw ( ) Tj
-117 -11.25 TD ( ) Tj
9.75 0 TD 0.2356 Tc -0.2731 Tw (We say that behavior is ) Tj
97.5 0 TD /F2 9.75 Tf
0.2423 Tc -0.4298 Tw (generally inconsistent) Tj
90.75 0 TD /F1 9.75 Tf
0.0884 Tc -0.0884 Tw ( when it is ) Tj
-198 -11.25 TD 0.1684 Tc 0.9566 Tw (incongruent with the user\222s general knowledge about the ) Tj
0 -11.25 TD 0.1347 Tc 7.9278 Tw (agent\222s purported personality, role and emotional) Tj
0 Tc -0.1875 Tw ( ) Tj
T* 0.1116 Tc -0.2991 Tw (disposition. In other word) Tj
103.5 0 TD 0.1626 Tc -0.3501 Tw (s, generally inconsistent behavior ) Tj
-103.5 -11.25 TD 0.1336 Tc -0.3211 Tw (is somehow \223out of character.\224) Tj
123.75 0 TD 0 Tc -0.1875 Tw ( ) Tj
-123.75 -11.25 TD ( ) Tj
9.75 0 TD 0.0994 Tc 2.9944 Tw (We can also delineate two forms of believable goal) Tj
0 Tc -0.1875 Tw ( ) Tj
-9.75 -11.25 TD 0.0895 Tc 2.723 Tw (coherency. Intra) Tj
68.25 0 TD -0.2467 Tc 0 Tw (-) Tj
3 0 TD 0.1512 Tc 1.6613 Tw (goal coherence deals with whether one ) Tj
-71.25 -11.25 TD 0.1199 Tc -0.2324 Tw (particular goal is itself understandable. To make sense of an ) Tj
0 -11.25 TD 0.2006 Tc 0.3619 Tw (agent\222s action, the) Tj
75.75 0 TD 0.2196 Tc -0.4071 Tw ( user must have ) Tj
65.25 0 TD /F2 9.75 Tf
-0.1341 Tc 0 Tw (some) Tj
20.25 0 TD /F1 9.75 Tf
0.1507 Tc -0.1507 Tw ( knowledge of both ) Tj
-161.25 -11.25 TD 0.2298 Tc 0.9463 Tw (the goals of the agent and how the actions contribute to ) Tj
0 -11.25 TD 0.2095 Tc 2.4363 Tw (those goals. This is an obvious, but often overlooked ) Tj
T* 0.0541 Tc 0.5084 Tw (requirement for all believable agents ) Tj
150 0 TD 0.0366 Tc 0.5259 Tw (\(Sengers 1998b\)) Tj
64.5 0 TD 0.2878 Tc -0.2253 Tw (. As a ) Tj
-214.5 -11.25 TD 0.2568 Tc 4.2432 Tw (caveat, one should note that) Tj
0 Tc 0.5625 Tw ( ) Tj
139.5 0 TD 0.1032 Tc 4.2092 Tw (in a real system, this) Tj
0 Tc 0.5625 Tw ( ) Tj
-139.5 -11.25 TD 0.1696 Tc 1.8179 Tw (constraint is far from strict. An agent that goes around ) Tj
0 -11.25 TD 0.1769 Tc 0.8856 Tw (announcing every one of its intentions would seem quite ) Tj
T* 0.1089 Tc 1.6723 Tw (silly; nevertheless, making goals evident is an important ) Tj
T* 0.1364 Tc 3.2118 Tw (and specific step that should be explicitly considered.) Tj
0 Tc -0.1875 Tw ( ) Tj
T* 0.2559 Tc -0.4434 Tw (When, ) Tj
36 0 TD 0.1134 Tc 5.8241 Tw (how often and in what manner intentional) Tj
0 Tc -0.1875 Tw ( ) Tj
-36 -11.25 TD 0.119 Tc 0.1708 Tw (information is communicated to the user is an issue that, in ) Tj
0 -11.25 TD 0.153 Tc -0.3405 Tw (most cases, would be determined by the character author. ) Tj
231.75 0 TD 0 Tc -0.1875 Tw ( ) Tj
-231.75 -11.25 TD ( ) Tj
9.75 0 TD 0.2184 Tc 0 Tw (Inter) Tj
18.75 0 TD -0.2467 Tc (-) Tj
3 0 TD 0.1713 Tc 1.8912 Tw (goal coherence is concerned whether the switch ) Tj
-31.5 -11.25 TD 0.1138 Tc 0.4487 Tw (from goal to goal has structure that makes) Tj
172.5 0 TD 0.2551 Tc -0.0676 Tw ( sense. Both the ) Tj
-172.5 -11.25 TD 0.1544 Tc 0.0331 Tw (agent\222s goal switches and lack of goal switches must seem ) Tj
0 -11.25 TD 0.1649 Tc 5.8618 Tw (rational. There should be some evident reason to) Tj
0 Tc 0.5625 Tw ( ) Tj
T* 0.1196 Tc 1.4929 Tw (necessitate the changing to a new goal. For example, an ) Tj
T* 0.0832 Tc 1.093 Tw (earlier goal may have been completed, or the new goal is ) Tj
T* 0.0186 Tc 1.2939 Tw (more important. Fur) Tj
81 0 TD 0.1029 Tc 0.4596 Tw (thermore, the agent may want to finish ) Tj
-81 -11.25 TD 0.1194 Tc 5.6931 Tw (old goals that are near completion, and/or resume) Tj
0 Tc -0.1875 Tw ( ) Tj
0 -11.25 TD 0.2606 Tc 6.3019 Tw (suspended old goals. Inter) Tj
126.75 0 TD -0.2467 Tc 0 Tw (-) Tj
3 0 TD 0.1702 Tc 6.3923 Tw (goal coherence is also) Tj
0 Tc 0.5625 Tw ( ) Tj
-129.75 -11.25 TD 0.146 Tc 1.6165 Tw (concerned with natural goal transitions ) Tj
169.5 0 TD 0.375 Tc 0 Tw (\226) Tj
5.25 0 TD 0.1626 Tc 1.1499 Tw ( this is what is ) Tj
0.0706 0.0706 0.0706 rg
ET
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h
f*
0.75 w
1 J
1 j
0 0 0 RG
95.25 203.25 m
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S
BT
103.5 201 TD
1 1 1 rg
/F4 5.6855 Tf
-0.01 Tc -0.0706 Tw (Goal 1) Tj
0.7843 0.7843 0.7843 rg
ET
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h
f*
156 249.75 m
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0 -11.25 TD 0.193 Tc 0.3695 Tw (agent to smoothly transition between the old goal and the ) Tj
T* 0.1743 Tc 0.3882 Tw (directed goal. To achieve this, the agent composes ) Tj
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0.1179 Tc -0.3054 Tw (a set of ) Tj
-210 -11.25 TD 0.2743 Tc 0 Tw (goals) Tj
22.5 0 TD /F1 9.75 Tf
0.2066 Tc 2.2309 Tw ( that would be reasonable to pursue. It can then ) Tj
-22.5 -11.25 TD 0.1702 Tc 0.3923 Tw (evaluate whether the t) Tj
90.75 0 TD 0.1527 Tc 0.0884 Tw (ransition from each of these goals to ) Tj
-90.75 -11.25 TD 0.1255 Tc 0.587 Tw (the directed goal is more natural than simply pursuing the ) Tj
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T* 0.187 Tc -0.3745 Tw (as a mediating goal and then repeat the process. ) Tj
194.25 0 TD 0 Tc -0.1875 Tw ( ) Tj
-194.25 -11.25 TD ( ) Tj
9.75 0 TD 0.0957 Tc 1.9668 Tw (To implement this extension, we need to deve) Tj
197.25 0 TD 0.1108 Tc 0.8267 Tw (lop two ) Tj
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3 0 TD 0 Tc -0.1875 Tw ( ) Tj
6.75 0 TD 0.0597 Tc 0.6902 Tw (First, we must create ) Tj
88.5 0 TD /F2 9.75 Tf
0.1984 Tc 0.3641 Tw (coherency heuristics) Tj
84.75 0 TD /F1 9.75 Tf
0.199 Tc 0.1135 Tw ( that evaluate ) Tj
-174 -11.25 TD 0.1544 Tc 0.1081 Tw (how smooth a transition between two goals may be. The ) Tj
0 -11.25 TD 0.2175 Tc 1.5116 Tw (agent needs these to decide whether one transition is ) Tj
T* 0.0954 Tc 0.0921 Tw (more coherent ) Tj
59.25 0 TD 0.2111 Tc -0.3986 Tw (than another.) Tj
53.25 0 TD 0 Tc -0.1875 Tw ( ) Tj
-121.5 -11.25 TD -0.2467 Tc 0 Tw (-) Tj
3 0 TD 0 Tc -0.1875 Tw ( ) Tj
6.75 0 TD 0.1128 Tc 2.3663 Tw (Second, we need to extend the standard HERB goal ) Tj
-0.75 -11.25 TD 0.1501 Tc 0.579 Tw (selection mechanism so that it can effectively use these ) Tj
0 -11.25 TD 0.1257 Tc -0.3132 Tw (heuristics to improvise the new goal into its behavior.) Tj
213.75 0 TD 0 Tc -0.1875 Tw ( ) Tj
-222.75 -11.25 TD 0.0748 Tc 0.8627 Tw (For the time being, we will leave out the issue of creating ) Tj
0 -11.25 TD 0.1506 Tc 2.6619 Tw (new transitioning go) Tj
88.5 0 TD 0.2343 Tc 1.7032 Tw (als. This topic has been addressed ) Tj
-88.5 -11.25 TD 0.1132 Tc 4.4993 Tw (extensively in Phoebe Sengers\222 thesis work) Tj
0 Tc -0.1875 Tw ( ) Tj
203.25 0 TD 0.1418 Tc 0.4207 Tw (\(Sengers ) Tj
-203.25 -11.25 TD -0.1376 Tc 0 Tw (1998a\)) Tj
25.5 0 TD 0.1074 Tc 3.4551 Tw (. Though we make no significant additions, her) Tj
0 Tc -0.1875 Tw ( ) Tj
-25.5 -11.25 TD 0.1097 Tc 2.5153 Tw (techniques would work quite well within our proposed ) Tj
0 -11.25 TD 0.1753 Tc -0.3628 Tw (system. ) Tj
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-33 -24.75 TD /F0 11.25 Tf
0.1538 Tc 0.0338 Tw (Goal Selection) Tj
70.5 0 TD 0 Tc 0.1875 Tw ( ) Tj
-70.5 -14.25 TD /F1 9.75 Tf
0.0503 Tc 3.5122 Tw (To improvise direction) Tj
97.5 0 TD 0.1767 Tc 3.1358 Tw (, we cannot select goals in the) Tj
0 Tc -0.1875 Tw ( ) Tj
-97.5 -11.25 TD 0.152 Tc 1.2439 Tw (standard HERBs fashion. We must change two facets of ) Tj
0 -11.25 TD 0.168 Tc 6.7159 Tw (the goal reasoning process, namely that of goal) Tj
0 Tc -0.1875 Tw ( ) Tj
T* 0.0283 Tc 2.4092 Tw (commitment and that of goal selection. Specifically, we ) Tj
T* 0.0995 Tc -0.062 Tw (must delay goal commitment and use our new heuristics for ) Tj
T* 0.1205 Tc -0.308 Tw (the final) Tj
32.25 0 TD 0.1151 Tc -0.3026 Tw ( goal selection. ) Tj
62.25 0 TD 0 Tc -0.1875 Tw ( ) Tj
-94.5 -11.25 TD ( ) Tj
9.75 0 TD 0.1621 Tc 0.829 Tw (A character\222s operator hierarchy outlines the reasoning ) Tj
-9.75 -11.25 TD 0.1615 Tc 2.201 Tw (that the agent could perform to achieve its goals. The ) Tj
265.5 629.25 TD 0.0666 Tc 0.7959 Tw (following is an excerpt from an operator hierarchy used in ) Tj
0 -11.25 TD 0.1405 Tc 1.172 Tw (one of the Soar QuakeBots, an action) Tj
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3 0 TD 0.2092 Tc 0.6033 Tw (oriented agent that ) Tj
-160.5 -11.25 TD 0.2416 Tc 0.3209 Tw (navigates ) Tj
41.25 0 TD 0.1337 Tc -0.3212 Tw (a virtual battlefield and battles other agents: ) Tj
177.75 0 TD 0 Tc -0.1875 Tw ( ) Tj
-219 -218.25 TD ( ) Tj
0 -11.25 TD 0.2001 Tc 0.5124 Tw (As illustrated, the agent decomposes high) Tj
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3 0 TD 0.1102 Tc 0.4523 Tw (level goals into ) Tj
-176.25 -11.25 TD 0.2054 Tc 7.3214 Tw (all possible subgoals that can contribute to its) Tj
0 Tc 0.5625 Tw ( ) Tj
0 -11.25 TD 0.1212 Tc 2.3163 Tw (achievement. Eventually, it is able to decompose these ) Tj
T* 0.1892 Tc 3.3733 Tw (goals into actions that describe either ho) Tj
185.25 0 TD 0.2142 Tc 2.0983 Tw (w the agent ) Tj
-185.25 -11.25 TD 0.0991 Tc 0.4634 Tw (changes its internal state or how it performs some external ) Tj
0 -11.25 TD 0.0908 Tc 2.9092 Tw (action. On any level, multiple goals may be proposed.) Tj
0 Tc -0.1875 Tw ( ) Tj
T* /F2 9.75 Tf
0.2119 Tc 0.3506 Tw (Preference knowledge) Tj
91.5 0 TD /F1 9.75 Tf
0.2653 Tc -0.2028 Tw ( is used to select and ) Tj
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0.091 Tc 0 Tw (commit) Tj
29.25 4.5 TD /F2 6 Tf
0 Tc (1) Tj
3 -4.5 TD /F1 9.75 Tf
0.3171 Tc -0.5046 Tw ( to one ) Tj
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57.75 0 TD 0.1509 Tc -0.3384 Tw (el, in which the agent may once again choose ) Tj
-57.75 -11.25 TD 0.1166 Tc -0.3041 Tw (another goal to commit to.) Tj
104.25 0 TD 0 Tc -0.1875 Tw ( ) Tj
-104.25 -11.25 TD 0.1295 Tc 0.733 Tw (We originally stated that to improvise, we want our agent ) Tj
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T* 0.2153 Tc 0 Tw (coherency) Tj
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43.5 0 TD 0.1502 Tc 1.4436 Tw (to choose between them. However, the way a ) Tj
-43.5 -11.25 TD 0.099 Tc 0.0885 Tw (standard HERB system works is that preference knowledge ) Tj
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9.75 0 TD /F2 9.75 Tf
0.2526 Tc 0.0599 Tw (only used to select among sibling goals) Tj
163.5 0 TD /F1 9.75 Tf
0.117 Tc -0.3045 Tw (. In other words, ) Tj
-173.25 -11.25 TD 0.1777 Tc 2.4473 Tw (it only chooses among the contextually possible goals ) Tj
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0.2686 Tc 1.0439 Tw (given the higher) Tj
69.75 0 TD -0.2467 Tc 0 Tw (-) Tj
3 0 TD 0.2084 Tc 0.9166 Tw (level goals it has committ) Tj
108.75 0 TD 0.3026 Tc 0.2599 Tw (ed to) Tj
21 0 TD /F1 9.75 Tf
-0.1631 Tc 0.4756 Tw (. We will ) Tj
-202.5 -11.25 TD 0.1476 Tc 1.3524 Tw (modify this so that coherency preference knowledge can ) Tj
0 -11.25 TD 0.1597 Tc 1.6982 Tw (potentially be used to select from any two goals in the ) Tj
T* 0.0978 Tc -0.2853 Tw (operator hierarchy. ) Tj
78 0 TD 0 Tc -0.1875 Tw ( ) Tj
-68.25 -11.25 TD 0.2383 Tc -0.0925 Tw (We do this as follows. We use our standard hand) Tj
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3 0 TD 0.2934 Tc 0.2691 Tw (coded ) Tj
-213.75 -11.25 TD 0.169 Tc 0.7269 Tw (preference knowledge to choose the best goal for a give) Tj
233.25 0 TD 0.375 Tc 0.1875 Tw (n ) Tj
-233.25 -11.25 TD 0.0942 Tc 0.8017 Tw (context. However, rather than committing to that goal and ) Tj
0 -11.25 TD 0.1475 Tc 0.6025 Tw (executing the next phase in the reasoning, we add it to an ) Tj
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0 Tc 0 Tw ( ) Tj
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( ) Tj
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(1) Tj
3 -4.5 TD /F1 9.75 Tf
0.0663 Tc -0.2538 Tw ( Please note that this commitment is not firm in the ) Tj
-3 -11.25 TD 0.1918 Tc -0.3793 Tw (intentional sense; rathe) Tj
93.75 0 TD 0.024 Tc -0.2115 Tw (r, it is a commitment to consider ) Tj
-93.75 -11.25 TD 0.1269 Tc -0.2311 Tw (only one particular level of the hierarchy when choosing ) Tj
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T* 0.1523 Tc -0.2773 Tw (if the context of the situation changes. It is only relevant to ) Tj
T* 0.225 Tc -0.4125 Tw (this discussion because it delineates the ) Tj
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-198.75 -11.25 TD ( ) Tj
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BT
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0.1461 Tc 1.6664 Tw (\223improvisation set\224 of goals. We then remove that goal ) Tj
0 -11.25 TD 0.1735 Tc 6.139 Tw (from consideration and use that same hand) Tj
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-213.75 -11.25 TD 0.1292 Tc 0.4333 Tw (preference knowledge to find anoth) Tj
144.75 0 TD 0.1888 Tc -0.2263 Tw (er goal to add, possibly ) Tj
-144.75 -11.25 TD 0.1233 Tc 1.4142 Tw (from another part of the operator hierarchy. This can be ) Tj
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17.25 0 TD 0 Tc -0.1875 Tw ( ) Tj
-17.25 -11.25 TD 0.078 Tc 0.6511 Tw ( To summarize, the standard HERB systems goal selection ) Tj
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0.1491 Tc 0.0384 Tw (Approach Overview) Tj
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-98.25 -14.25 TD /F1 9.75 Tf
0.2463 Tc -0.4338 Tw (The first phase consists of a hand) Tj
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3 0 TD 0.1734 Tc -0.1734 Tw (coded expert system that ) Tj
-138.75 -11.25 TD 0.0717 Tc 1.8033 Tw (uses a hierarchical decision making mechanism found in ) Tj
0 -11.25 TD 0.0877 Tc 6.0463 Tw (similar agents we have created for other dynamic) Tj
0 Tc -0.1875 Tw ( ) Tj
T* 0.1392 Tc 0.4233 Tw (environments ) Tj
57.75 0 TD -0.0218 Tc 0.2093 Tw (\(Laird and Duchi 2000; Laird and Jones 1998; ) Tj
-57.75 -11.25 TD -0.1746 Tc 1.4871 Tw (Laird et al 1999\)) Tj
66.75 0 TD 0.147 Tc 0.5821 Tw (. What is different is that, rather than just ) Tj
-66.75 -11.25 TD 0.2222 Tc 4.0903 Tw (propose and apply an operator, the agent creates a) Tj
0 Tc -0.1875 Tw ( ) Tj
0 -11.25 TD 0.1288 Tc 5.3623 Tw (declarative representation of a goal. We call these) Tj
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3 0 TD 0.2148 Tc 4.0977 Tw (dependent declarative data structur) Tj
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0 Tc 0.5625 Tw ( ) Tj
-207 -11.25 TD 0.1983 Tc 0.8142 Tw (specify a goal and possibly some additional data such as ) Tj
0 -11.25 TD 0.0829 Tc 0.3725 Tw (summary information or the results of any problem) Tj
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3 0 TD 0.1837 Tc 0.3788 Tw (solving ) Tj
-208.5 -11.25 TD 0.0994 Tc 0.3131 Tw (that occurred when the PIG was added. This information is ) Tj
0 -11.25 TD 0.0729 Tc 0.3959 Tw (important because it will facilitate the upcoming coherency ) Tj
T* 0.1656 Tc 1.8969 Tw (evaluations. Th) Tj
64.5 0 TD 0.2543 Tc 1.3082 Tw (e agent can then generate a set of these ) Tj
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174 0 TD 0 Tc -0.1875 Tw ( ) Tj
-174 -11.25 TD ( ) Tj
9.75 0 TD 0.2899 Tc 1.3976 Tw (The second phase consists of an inter) Tj
163.5 0 TD -0.2467 Tc 0 Tw (-) Tj
3 0 TD 0.1688 Tc 0.3937 Tw (goal coherence ) Tj
-176.25 -11.25 TD 0.2074 Tc 1.7613 Tw (advocate, which operates between the abstract tasks of ) Tj
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37.5 0 TD 0.2162 Tc 0.2525 Tw ( agent have coherent transitions between the last ) Tj
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42 0 TD -0.2467 Tc (-) Tj
3 0 TD 0.1204 Tc 1.9421 Tw (based preference knowledge. This knowledge ) Tj
-45 -11.25 TD 0.2374 Tc 0.2001 Tw (allows the agent to choose the ) Tj
129 0 TD 0.0475 Tc 0.515 Tw (PIG that, if pursued, would ) Tj
-129 -11.25 TD 0.1762 Tc 1.6363 Tw (result in the most coherent behavior given the previous ) Tj
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159.75 0 TD -0.2467 Tc 0 Tw (-) Tj
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-162.75 -11.25 TD 0.1151 Tc -0.3026 Tw (goal ) Tj
19.5 0 TD 0.0307 Tc -0.2182 Tw (that will make for a smoother transition. ) Tj
159 0 TD 0 Tc -0.1875 Tw ( ) Tj
-178.5 -11.25 TD ( ) Tj
9.75 0 TD 0.129 Tc 1.1835 Tw (The third phase contains the improvisational execution ) Tj
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265.5 455.25 TD 0.2313 Tc 4.724 Tw (of the situation and a set of appropr) Tj
179.25 0 TD 0.0395 Tc 4.273 Tw (iate execution) Tj
0 Tc 0.5625 Tw ( ) Tj
-179.25 -11.25 TD 0.083 Tc 1.3233 Tw (knowledge, the agent performs primitive actions to effect ) Tj
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0 Tc -0.1875 Tw ( ) Tj
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119.25 0 TD 0.1394 Tc -0.5144 Tw (these attributes, the algorithm ) Tj
-119.25 -11.25 TD 0.2109 Tc 0.0516 Tw (chooses actions that both meet the goals and are generally ) Tj
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152.25 0 TD 0 Tc -0.1875 Tw ( ) Tj
-152.25 -11.25 TD ( ) Tj
9.75 0 TD 0.1775 Tc 6.2778 Tw (There are three main advantages to using this) Tj
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-96 -11.25 TD 0.174 Tc 3.576 Tw (used as time permits. Without any use of coherence) Tj
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45.75 0 TD 0.0882 Tc 2.8314 Tw (ly improve the believability of our standard ) Tj
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86.25 0 TD 0.2018 Tc 1.0035 Tw (n behind our heuristics is that goals ) Tj
-86.25 -11.25 TD 0.1229 Tc 0.1063 Tw (that are similar on some dimension produce transitions that ) Tj
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100.5 0 TD /F1 9.75 Tf
0.1641 Tc 0.2734 Tw (: This heuristic uses the default ) Tj
-92.25 -11.25 TD 0.1873 Tc 2.3752 Tw (preferences in the oper) Tj
99.75 0 TD 0.1021 Tc 1.9604 Tw (ator hierarchy, i.e. the hand) Tj
117.75 0 TD -0.2467 Tc 0 Tw (-) Tj
-217.5 -11.25 TD 0.1313 Tc 0.8062 Tw (encoded preference knowledge, as a measure of what ) Tj
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0.0214 Tc -0.2089 Tw (Figure ) Tj
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-0.2813 Tc 0 Tw (2.) Tj
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3 0 TD /F0 9.75 Tf
-0.0852 Tc 2.8977 Tw (Goal hierarchy distance) Tj
103.5 0 TD /F1 9.75 Tf
0.1306 Tc 1.7819 Tw (: This heuristic leverages the ) Tj
-95.25 -11.25 TD 0.1153 Tc 0.4472 Tw (hierarchical structure of the goal operator hierarchy to ) Tj
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142.5 0 TD 0.1109 Tc 0.3016 Tw (r two goals may be ) Tj
-142.5 -11.25 TD 0.1633 Tc 0.5492 Tw (by measuring how \223near\224 one goal is to another. The ) Tj
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T* 0.0965 Tc 2.9973 Tw (Similarly, goals that subsume each other are very ) Tj
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0.1542 Tc 6.4083 Tw (: This heuristic generates an) Tj
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-81 -11.25 TD 0.1079 Tc 4.3296 Tw (evaluation based on summary information of the) Tj
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0 -11.25 TD 0.124 Tc 1.751 Tw (primitive actions that the given goals may produce. ) Tj
T* 0.1542 Tc 1.8249 Tw (The premise behind this heuristic is that using two ) Tj
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0 Tc -0.1875 Tw ( ) Tj
T* -0.2265 Tc 0.039 Tw (similar ) Tj
28.5 0 TD 0.1136 Tc 0.1676 Tw (actions. This may make any transition harder to ) Tj
-28.5 -11.25 TD 0.1458 Tc -0.3333 Tw (detect. Such activity may even appear synergistic.) Tj
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0.1965 Tc 0.366 Tw (: We can annotate the goals with ) Tj
-84.75 -11.25 TD 0.1849 Tc -0.289 Tw (some knowledge about the type of goal being pursued. ) Tj
0 -11.25 TD 0.1745 Tc 2.4713 Tw (This could range from task classes to the various ) Tj
T* 0.171 Tc 0 Tw (a) Tj
4.5 0 TD 0.1611 Tc 0.2942 Tw (ttributes of general consistency. Using this heuristic, ) Tj
-4.5 -11.25 TD 0.1504 Tc 0.7872 Tw (we can measure transition coherency on that specific ) Tj
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0 Tc -0.1875 Tw ( ) Tj
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0.171 Tc -0.3585 Tw (\224 ) Tj
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-0.1875 Tc 0 Tw (.) Tj
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-236.25 -11.25 TD ( ) Tj
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0.1616 Tc 4.6509 Tw (to attack based on whether it hates, dislikes or ) Tj
4.0395 Tc 0 Tw (i) Tj
234 0 TD 0.7072 Tc -0.1447 Tw (s ) Tj
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0.1251 Tc 1.4017 Tw ( By moving some of the proposal ) Tj
-94.5 -11.25 TD 0.1117 Tc 1.2946 Tw (knowledge into preference knowledge, we give the agent ) Tj
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T* 0.3987 Tc 0.9138 Tw (must s) Tj
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T* 0.2365 Tc -0.424 Tw (system contributed to any resul) Tj
126.75 0 TD 0.177 Tc -0.3645 Tw (ts that may be achieved. ) Tj
99 0 TD 0 Tc -0.1875 Tw ( ) Tj
-225.75 -11.25 TD ( ) Tj
9.75 0 TD 0.1478 Tc 0.6874 Tw (To make progress in this research area, we need to pay ) Tj
-9.75 -11.25 TD 0.1518 Tc 5.9821 Tw (more attention to this issue of credit assignment.) Tj
0 Tc -0.1875 Tw ( ) Tj
0 -11.25 TD 0.0758 Tc 0.8081 Tw (Furthermore, we must develop concrete evaluation criteria ) Tj
T* 0.1636 Tc -0.3511 Tw (for evaluating coherency.) Tj
102 0 TD 0 Tc -0.1875 Tw ( ) Tj
-102 -24.75 TD /F0 11.25 Tf
-0.1021 Tc 0.2896 Tw (Experimental Variations) Tj
118.5 0 TD 0 Tc 0.1875 Tw ( ) Tj
-118.5 -14.25 TD /F1 9.75 Tf
0.0241 Tc -0.2116 Tw (To test the imp) Tj
60 0 TD 0.1616 Tc -0.3491 Tw (act of various components, we plan to create ) Tj
-60 -11.25 TD 0.109 Tc 1.2868 Tw (several different variations of the algorithm and see how ) Tj
0 -11.25 TD 0.1359 Tc -0.3234 Tw (the quality of the behavior differs.) Tj
135.75 0 TD 0 Tc -0.1875 Tw ( ) Tj
-135.75 -11.25 TD -0.2813 Tc 0 Tw (1.) Tj
6.75 0 TD 0 Tc -0.1875 Tw ( ) Tj
3 0 TD ( ) Tj
8.25 0 TD 0.0505 Tc 0.1787 Tw (We will try different sized improvisation sets. Our goal ) Tj
0 -11.25 TD 0.0996 Tc 0.8379 Tw (is to examine the relationship between increased goal ) Tj
T* 0.3322 Tc 0 Tw (opti) Tj
15.75 0 TD 0.1241 Tc 0.3551 Tw (ons and quality of improvised behavior, as well as ) Tj
-15.75 -11.25 TD 0.0871 Tc 0.9442 Tw (how much computational load increases with a larger ) Tj
0 -11.25 TD -0.3136 Tc 0.1261 Tw (PIG limit.) Tj
35.25 0 TD 0 Tc -0.1875 Tw ( ) Tj
-53.25 -11.25 TD -0.2813 Tc 0 Tw (2.) Tj
6.75 0 TD 0 Tc -0.1875 Tw ( ) Tj
3 0 TD ( ) Tj
8.25 0 TD 0.0351 Tc 0.9774 Tw (We will also try different ways of increasing the limit ) Tj
0 -11.25 TD 0.2492 Tc 1.5883 Tw (and see how that affects the answers to the above ) Tj
T* 0.0689 Tc 3.6437 Tw (questions. For example, we can iter) Tj
158.25 0 TD 0.1614 Tc 3.4011 Tw (atively change) Tj
0 Tc -0.1875 Tw ( ) Tj
-158.25 -11.25 TD 0.0474 Tc 4.1579 Tw (proposal limit when direction is received, until a) Tj
0 Tc -0.1875 Tw ( ) Tj
0 -11.25 TD 0.1647 Tc -0.3522 Tw (sufficiently good goal is found.) Tj
125.25 0 TD 0 Tc -0.1875 Tw ( ) Tj
-143.25 -11.25 TD -0.2813 Tc 0 Tw (3.) Tj
6.75 0 TD 0 Tc -0.1875 Tw ( ) Tj
3 0 TD ( ) Tj
8.25 0 TD 0.0125 Tc 6.55 Tw (We will experiment with both the number of) Tj
0 Tc -0.1875 Tw ( ) Tj
0 -11.25 TD -0.0019 Tc -0.1856 Tw (intermediate PIGs permitted.) Tj
111.75 0 TD 0 Tc -0.1875 Tw ( ) Tj
-129.75 -11.25 TD -0.2813 Tc 0 Tw (4.) Tj
6.75 0 TD 0 Tc -0.1875 Tw ( ) Tj
3 0 TD ( ) Tj
8.25 0 TD 0.1399 Tc 0.9851 Tw (Since we have multiple types of coherence advocacy ) Tj
0 -11.25 TD 0.1525 Tc 1.01 Tw (strategies, we must isolate and ) Tj
132 0 TD 0.1997 Tc 0.0628 Tw (test each one of them ) Tj
-132 -11.25 TD 0.0524 Tc 0 Tw (individually.) Tj
49.5 0 TD 0 Tc -0.1875 Tw ( ) Tj
-67.5 -11.25 TD -0.2813 Tc 0 Tw (5.) Tj
6.75 0 TD 0 Tc -0.1875 Tw ( ) Tj
3 0 TD ( ) Tj
8.25 0 TD 0.1279 Tc 0.2679 Tw (Furthermore, since only a portion of the heuristics can ) Tj
0 -11.25 TD 0.1242 Tc 0.4383 Tw (be used in a given time period, we must also consider ) Tj
T* 0.1392 Tc 1.6233 Tw (the ordering of their use. Moreover, we can try the ) Tj
T* -0.0659 Tc 3.9499 Tw (algorithm with the artificial luxury of infinite time) Tj
0 Tc -0.1875 Tw ( ) Tj
265.5 618 TD 0.239 Tc 0 Tw (ava) Tj
14.25 0 TD 0.0467 Tc 2.9158 Tw (ilable to see how well it would do in an ideal) Tj
0 Tc -0.1875 Tw ( ) Tj
-14.25 -11.25 TD 0.2224 Tc 0 Tw (situation.) Tj
37.5 0 TD 0 Tc -0.1875 Tw ( ) Tj
-55.5 -11.25 TD -0.2813 Tc 0 Tw (6.) Tj
6.75 0 TD 0 Tc -0.1875 Tw ( ) Tj
3 0 TD ( ) Tj
8.25 0 TD 0.2651 Tc 6.6724 Tw (When the inter) Tj
74.25 0 TD -0.2467 Tc 0 Tw (-) Tj
3 0 TD 0.182 Tc 6.3805 Tw (goal coherency cannot find a) Tj
0 Tc -0.1875 Tw ( ) Tj
-77.25 -11.25 TD 0.1383 Tc 3.1242 Tw (sufficiently smooth transition among the candidate) Tj
0 Tc -0.1875 Tw ( ) Tj
0 -11.25 TD 0.0886 Tc 3.6614 Tw (PIGs, it resorts to adding a mediating goal. This) Tj
0 Tc 0.5625 Tw ( ) Tj
T* 0.1498 Tc 1.2564 Tw (threshold value, which is closely related to the ope) Tj
215.25 0 TD 0.375 Tc 0.1875 Tw (n ) Tj
-215.25 -11.25 TD 0.1764 Tc 1.6361 Tw (research question of how to combine the results of ) Tj
0 -11.25 TD -0.0301 Tc -0.1574 Tw (multiple heuristics, is a value we will explore. ) Tj
179.25 0 TD 0 Tc -0.1875 Tw ( ) Tj
-197.25 -11.25 TD -0.2813 Tc 0 Tw (7.) Tj
6.75 0 TD 0 Tc -0.1875 Tw ( ) Tj
3 0 TD ( ) Tj
8.25 0 TD 0.0615 Tc 1.476 Tw (The algorithm also places time limits on each of the ) Tj
0 -11.25 TD 0.1103 Tc 2.5356 Tw (phases. We need to examine the manner in which ) Tj
T* 0.136 Tc 3.6408 Tw (changes to those time limits affects the resulting) Tj
0 Tc 0.5625 Tw ( ) Tj
T* 0.375 Tc 0 Tw (b) Tj
5.25 0 TD 0.0715 Tc (ehavior.) Tj
32.25 0 TD 0 Tc -0.1875 Tw ( ) Tj
-55.5 -11.25 TD -0.2813 Tc 0 Tw (8.) Tj
6.75 0 TD 0 Tc -0.1875 Tw ( ) Tj
3 0 TD ( ) Tj
8.25 0 TD 0.2031 Tc -0.0692 Tw (We also plan to compare a standard hand) Tj
168 0 TD -0.2467 Tc 0 Tw (-) Tj
3 0 TD 0.2849 Tc -0.0974 Tw (coded agent ) Tj
-171 -11.25 TD 0.1166 Tc 0.3626 Tw (to a neutered version of the improvisational agent, i.e. ) Tj
0 -11.25 TD 0.0881 Tc 1.8244 Tw (PIG limit of 1 and no advocates, to investigate two ) Tj
T* 0.1616 Tc 2.6509 Tw (issues. The goal is to examine both the overhead ) Tj
T* 0.2149 Tc 0.3476 Tw (introduced by our approach and wheth) Tj
159.75 0 TD 0.1457 Tc -0.0832 Tw (er the behavior ) Tj
-159.75 -11.25 TD -0.033 Tc -0.1545 Tw (will differ with the knowledge) Tj
117 0 TD -0.2467 Tc 0 Tw (-) Tj
3 0 TD 0.2076 Tc -0.3951 Tw (restructured agent?) Tj
78 0 TD 0 Tc -0.1875 Tw ( ) Tj
-216 -24.75 TD /F0 11.25 Tf
-0.0694 Tc 0.2569 Tw (Evaluation Criteria) Tj
93 0 TD 0 Tc 0.1875 Tw ( ) Tj
-93 -14.25 TD /F1 9.75 Tf
0.174 Tc 0.6135 Tw (One way to evaluate the effectiveness of this approach id ) Tj
0 -11.25 TD 0.092 Tc 2.1371 Tw (to develop metrics that may indirectly correlate to how ) Tj
T* 0.0721 Tc 1.4279 Tw (coherent the behavior generated is. For example, we may) Tj
238.5 0 TD 0 Tc -0.1875 Tw ( ) Tj
-238.5 -11.25 TD 0.1002 Tc 1.9623 Tw (examine the number of imposed goal switches an agent ) Tj
0 -11.25 TD 0.1233 Tc 1.4142 Tw (takes to achieve a direction. One could argue that fewer ) Tj
T* 0.1663 Tc 0.7712 Tw (switches indicate more consistent and coherent behavior. ) Tj
T* 0.0814 Tc 1.3061 Tw (Another metric we are considering is the amount of time ) Tj
T* 0.1791 Tc 0.2584 Tw (spent in a portion of operator ) Tj
123.75 0 TD 0.0545 Tc -0.092 Tw (hierarchy. A large number of ) Tj
-123.75 -11.25 TD 0.1488 Tc -0.2 Tw (abrupt switches from one portion of the tree to another may ) Tj
0 -11.25 TD 0.1421 Tc -0.3296 Tw (be indicative of less coherent behavior. ) Tj
159 0 TD 0 Tc -0.1875 Tw ( ) Tj
-159 -11.25 TD ( ) Tj
9.75 0 TD 0.2128 Tc 6.5997 Tw (Another way to evaluate coherency is through) Tj
0 Tc 0.5625 Tw ( ) Tj
-9.75 -11.25 TD 0.1473 Tc 2.1964 Tw (subjective means. Wilkins and desJardins argue that in ) Tj
0 -11.25 TD 0.0129 Tc 2.7996 Tw (realistic domains, evalu) Tj
99 0 TD 0.0864 Tc 1.8261 Tw (ating plans is frequently difficult ) Tj
-99 -11.25 TD 0.1678 Tc -0.2719 Tw (since \223humans often have evaluation criteria that cannot be ) Tj
0 -11.25 TD 0.1592 Tc 4.6033 Tw (captured precisely and commonsense knowledge that) Tj
0 Tc 0.5625 Tw ( ) Tj
T* 0.1151 Tc 1.6661 Tw (allows them to determine appropriate actions in unusual ) Tj
T* 0.1723 Tc 2.7339 Tw (situations that were unforeseen when the domain was ) Tj
T* -0.9803 Tc 0 Tw (mo) Tj
12 0 TD 0.1338 Tc -0.3213 Tw (deled\224 ) Tj
29.25 0 TD 0.0358 Tc 0.0267 Tw (\(Wilkins and desJardins 2001\)) Tj
120 0 TD -0.1089 Tc -0.0786 Tw (. Similarly, there are ) Tj
-161.25 -11.25 TD 0.1655 Tc 1.147 Tw (many aesthetic or more abstract facets of coherency that ) Tj
0 -11.25 TD 0.0411 Tc -0.2286 Tw (are hard to capture numerically or symbolically. ) Tj
190.5 0 TD 0 Tc -0.1875 Tw ( ) Tj
-190.5 -11.25 TD ( ) Tj
9.75 0 TD 0.0649 Tc 0.3101 Tw (Users who participate in the interactive environment will ) Tj
-9.75 -11.25 TD 0.0915 Tc 4.221 Tw (be able to giv) Tj
67.5 0 TD 0.1681 Tc 3.3944 Tw (e feedback on what they found either) Tj
0 Tc -0.1875 Tw ( ) Tj
-67.5 -11.25 TD 0.143 Tc 0.8968 Tw (successful or problematic. One way to do this is to place ) Tj
0 -11.25 TD 0.1914 Tc 0.5586 Tw (the user in the environments and ask them to hit a button ) Tj
T* 0.1905 Tc 0.5595 Tw (when he or she thinks an agent is being directed. We can ) Tj
T* 0.2093 Tc 1.2699 Tw (then compare this data to when and how the goa) Tj
209.25 0 TD 0.0088 Tc 0.5537 Tw (ls were ) Tj
-209.25 -11.25 TD 0.1863 Tc -0.3738 Tw (selected in the agent. ) Tj
87 0 TD 0 Tc -0.1875 Tw ( ) Tj
-87 -11.25 TD ( ) Tj
9.75 0 TD 0.196 Tc 0.0332 Tw (Another way we can generate subjective data is through ) Tj
-9.75 -11.25 TD 0.3214 Tc 4.7411 Tw (post run) Tj
39 0 TD -0.2467 Tc 0 Tw (-) Tj
3 0 TD 0.1303 Tc 4.2893 Tw (time surveys. A good example of such an) Tj
0 Tc 0.5625 Tw ( ) Tj
-42 -11.25 TD 0.2099 Tc 0.3526 Tw (approach can be found in ) Tj
108 0 TD -0.4715 Tc 0 Tw (\(El) Tj
10.5 0 TD -0.2467 Tc (-) Tj
3 0 TD -0.0949 Tc 0.6574 Tw (Nasr et al 1999\)) Tj
63 0 TD 0.0107 Tc -0.1982 Tw (. In this work, ) Tj
-184.5 -11.25 TD -0.5839 Tc 0 Tw (El) Tj
7.5 0 TD -0.2467 Tc (-) Tj
3 0 TD 0.089 Tc 0.6235 Tw (Nasr attempts to evaluate a fuzzy) Tj
136.5 0 TD -0.2467 Tc 0 Tw (-) Tj
3 0 TD 0.1447 Tc (logi) Tj
15 0 TD 0.1313 Tc 0.1812 Tw (c based emotional ) Tj
-165 -11.25 TD 0.178 Tc 0.0511 Tw (model. A survey asks users to evaluate several dimensions ) Tj
0 -11.25 TD 0.2191 Tc 0.8434 Tw (of the agent\222s behavior on a ten) Tj
135 0 TD -0.2467 Tc 0 Tw (-) Tj
3 0 TD 0.1778 Tc 0.2347 Tw (point scale. This is done ) Tj
-138 -11.25 TD 0.1661 Tc 0.7714 Tw (for three versions of the system: the standard model, one ) Tj
0 -11.25 TD 0.0961 Tc 2.8101 Tw (with learning and one that has completely randomized ) Tj
T* 0.1053 Tc -0.2928 Tw (behavior. ) Tj
42 0 TD 0.1358 Tc 1.0696 Tw (They then compared the systems by examining ) Tj
-42 -11.25 TD 0.1036 Tc 1.2089 Tw (how well each did compared to the average value with a ) Tj
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54 729 TD
0 0 0 rg
/F1 9.75 Tf
0.153 Tc 0.8262 Tw (confidence interval of 95%. Though based on subjective ) Tj
0 -11.25 TD 0.1025 Tc 2.2933 Tw (feedback, we could also use similar methods to isolate ) Tj
T* 0.1364 Tc 4.1761 Tw (statistically significant trends that can poin) Tj
195 0 TD 0.3384 Tc 3.9741 Tw (t to both) Tj
0 Tc 0.5625 Tw ( ) Tj
-195 -11.25 TD 0.0857 Tc -0.2732 Tw (successful and problematic areas of our algorithm.) Tj
200.25 0 TD 0 Tc -0.1875 Tw ( ) Tj
-110.25 -32.25 TD /F0 12 Tf
0.1782 Tc 0 Tw (References) Tj
57.75 0 TD 0 Tc ( ) Tj
-147.75 -18 TD /F1 9 Tf
-0.0082 Tc 1.6957 Tw (Bates J, Loyall A B, Reilly W S, 1992a "An Architecture for ) Tj
9.75 -11.25 TD -0.0755 Tc 0.0755 Tw (Action, Emotion and Social Behavior") Tj
136.5 0 TD 0 Tc 0 Tw ( ) Tj
-146.25 -11.25 TD -0.022 Tc 0.9766 Tw (Bates J, Loyall A B, Reilly W S, 1992b "Integrating Reactivity, ) Tj
9.75 -11.25 TD 0 Tc -0 Tw (Goals, ) Tj
25.5 0 TD -0.0276 Tc 0.0276 Tw (and Emotion in a Broad Agent") Tj
112.5 0 TD 0 Tc 0 Tw ( ) Tj
-147.75 -11.25 TD -0.0249 Tc 1.5931 Tw (Bates J, Loyall B, Reilly W S, 1991 "Broad Agents", in ) Tj
219.75 0 TD /F2 9 Tf
-0.186 Tc 0.186 Tw (AAAI ) Tj
-210 -11.25 TD -0.083 Tc 0.083 Tw (Spring Symposium on Integrated Intelligent Architectures) Tj
204.75 0 TD /F1 9 Tf
0 Tc 0 Tw ( ) Tj
2.25 0 TD ( ) Tj
-216.75 -11.25 TD -0.2505 Tc (El) Tj
7.5 0 TD 0.003 Tc (-) Tj
3 0 TD 0.0143 Tc 1.1396 Tw (Nasr M S, Ioerger T R, Yen J, 1999 "PETEEI: A PET with ) Tj
-0.75 -11.25 TD -0.1339 Tc 0.1339 Tw (Evolving Emotional Intelligence", in ) Tj
130.5 0 TD /F2 9 Tf
-0.0207 Tc 0.0207 Tw (Autonomous Ag) Tj
57 0 TD -0.2498 Tc 0 Tw (ents) Tj
14.25 0 TD /F1 9 Tf
0 Tc ( ) Tj
2.25 0 TD ( ) Tj
-213.75 -11.25 TD 0.0529 Tc 0.2933 Tw (Freed M, Bear T, Goldman H, Hyatt G, Reber P, Tauber J, 2000 ) Tj
9.75 -11.25 TD -0.0092 Tc 3.0092 Tw ("Towards more human) Tj
88.5 0 TD 0.003 Tc 0 Tw (-) Tj
3 0 TD 0.0634 Tc 2.1866 Tw (like computer opponents", in ) Tj
119.25 0 TD /F2 9 Tf
0 Tc 0 Tw (1999 ) Tj
-210.75 -11.25 TD -0.0545 Tc 0.0545 Tw (AAAI Spring Symposium on AI and Interactive Entertainment) Tj
219 0 TD /F1 9 Tf
0 Tc 0 Tw ( ) Tj
2.25 0 TD ( ) Tj
-231 -11.25 TD 0.0018 Tc (Hayes) Tj
23.25 0 TD 0.003 Tc (-) Tj
3 0 TD 0.0171 Tc 5.2329 Tw (Roth B, Doyle P, 1998 "Animate Characters", in) Tj
0 Tc 0 Tw ( ) Tj
-16.5 -11.25 TD /F2 9 Tf
-0.0262 Tc 3.2762 Tw (Autonomous Agents and ) Tj
3.003 Tc 0 Tw (M) Tj
106.5 0 TD -0.189 Tc (ulti) Tj
11.25 0 TD 0.003 Tc (-) Tj
3 0 TD -0.0617 Tc 3.0618 Tw (Agent Systems) Tj
54 0 TD /F1 9 Tf
-0.0182 Tc 1.5182 Tw ( \(Netherlands: ) Tj
-174.75 -11.25 TD 0.0891 Tc -0.0891 Tw (Netherlands\) pp 195) Tj
75 0 TD 0.003 Tc 0 Tw (-) Tj
3 0 TD 0 Tc (230) Tj
13.5 0 TD ( ) Tj
-101.25 -11.25 TD 0.0018 Tc (Hayes) Tj
23.25 0 TD 0.003 Tc (-) Tj
3 0 TD 0.0867 Tc -0.0034 Tw (Roth B, Gent R v, 1996 "Improvisational Puppets, Actors ) Tj
-16.5 -11.25 TD 0.0285 Tc -0.0285 Tw (and Avatars", ) Tj
51.75 0 TD 0 Tc 0 Tw ( ) Tj
-61.5 -11.25 TD 0.0018 Tc (Hayes) Tj
23.25 0 TD 0.003 Tc (-) Tj
3 0 TD 0.0295 Tc 2.2205 Tw (Roth B, Rousseau D, 1997 "Improvisational Synthetic ) Tj
-16.5 -11.25 TD -0.0203 Tc 0.0203 Tw (Actors with Flexible Personalities", ) Tj
129.75 0 TD 0 Tc 0 Tw ( ) Tj
-139.5 -11.25 TD -0.022 Tc 0.2095 Tw (Laird J, Assanie M, Bachel) Tj
98.25 0 TD -0.0665 Tc 0.0665 Tw (or B, Benninghoff N, Enam S, Jones B, ) Tj
-88.5 -11.25 TD -0.0285 Tc 3.1951 Tw (Kerfoot A, Lauver C, Magerko B, Sheiman J, Stokes D,) Tj
0 Tc 0 Tw ( ) Tj
0 -11.25 TD -0.0628 Tc 4.7771 Tw (Wallace S, 2002 "A Testbed for Developing Intelligent) Tj
0 Tc 0.75 Tw ( ) Tj
T* 0.0039 Tc 0.4961 Tw (Synthetic Characters", in ) Tj
94.5 0 TD /F2 9 Tf
-0.0726 Tc 0.3726 Tw (AAAI Spring Symposium on Artificial ) Tj
-94.5 -11.25 TD -0.1019 Tc 0.1019 Tw (Intelligence and Interactive Entertainment) Tj
149.25 0 TD /F1 9 Tf
-0.041 Tc 0.041 Tw ( \(Stanf) Tj
24 0 TD 0.0538 Tc -0.0538 Tw (ord University: ) Tj
-173.25 -11.25 TD 0.0399 Tc -0.0399 Tw (Stanford University\) ) Tj
77.25 0 TD 0 Tc 0 Tw ( ) Tj
-87 -11.25 TD -0.0503 Tc 4.336 Tw (Laird J, Duchi J C, 2000 "Creating Human) Tj
182.25 0 TD 0.003 Tc 0 Tw (-) Tj
3 0 TD -0.0194 Tc 3.7694 Tw (like Synthetic) Tj
0 Tc 0 Tw ( ) Tj
-175.5 -11.25 TD -0.0096 Tc 0.2141 Tw (Characters with Multiple Skill Levels: A Case Study using the ) Tj
0 -11.25 TD -0.0414 Tc 2.0414 Tw (Soar Quakebot", in ) Tj
79.5 0 TD /F2 9 Tf
-0.0513 Tc 2.5513 Tw (AAAI 2000 Fall Symposium Series on ) Tj
-79.5 -11.25 TD -0.0714 Tc 0.0714 Tw (Simulating Human Agents) Tj
93.75 0 TD /F1 9 Tf
0 Tc 0 Tw ( ) Tj
2.25 0 TD ( ) Tj
-105.75 -11.25 TD 0.0502 Tc 1.1498 Tw (Laird J, Jones R M, ) Tj
81 0 TD -0.0277 Tc 0.7777 Tw (1998 "Building Advanced Autonomous AI ) Tj
-71.25 -11.25 TD -0.0992 Tc 1.2242 Tw (Systems for Large) Tj
67.5 0 TD 0.003 Tc 0 Tw (-) Tj
3 0 TD -0.249 Tc 0.999 Tw (Scale Real) Tj
36.75 0 TD 0.003 Tc 0 Tw (-) Tj
3 0 TD -0.0755 Tc 0.5755 Tw (Time Simulations", in ) Tj
82.5 0 TD /F2 9 Tf
0 Tc -0 Tw (Computer ) Tj
-192.75 -11.25 TD -0.0195 Tc 0.0195 Tw (Game Developers Conference) Tj
108 0 TD /F1 9 Tf
0 Tc 0 Tw ( ) Tj
2.25 0 TD ( ) Tj
-120 -11.25 TD 0.064 Tc 0.386 Tw (Laird J E, Coulter K J, Jones R M, Kenny P G, Koss F, Nielson ) Tj
9.75 -11.25 TD -0.0089 Tc 2.1756 Tw (P E, 1999 "Automated Intelligent Pilots for Combat Flight ) Tj
0 -11.25 TD -0.126 Tc 0 Tw (Simulation) Tj
38.25 0 TD -0.0435 Tc 0.0435 Tw (", in ) Tj
17.25 0 TD /F2 9 Tf
-0.0492 Tc 0.0492 Tw (AI Magazine) Tj
45.75 0 TD /F1 9 Tf
0.375 Tc -0.375 Tw ( pp 27) Tj
24 0 TD 0.003 Tc 0 Tw (-) Tj
3 0 TD 0 Tc (42) Tj
9 0 TD ( ) Tj
-147 -11.25 TD -0.0243 Tc 1.6607 Tw (Reilly W S, 1994 "The Art of Creating Emotional and Robust ) Tj
9.75 -11.25 TD -0.017 Tc 0.017 Tw (Interactive Characters", ) Tj
87 0 TD 0 Tc 0 Tw ( ) Tj
-96.75 -11.25 TD -0.0579 Tc 0.0579 Tw (Reilly W S, Bates J, 1992 "Building Emotional Agents") Tj
198.75 0 TD 0 Tc 0 Tw ( ) Tj
-198.75 -11.25 TD -0.0967 Tc 0.0967 Tw (Reilly W S N, 1996 "Believable Social and Emotional Agents") Tj
222 0 TD 0 Tc 0 Tw ( ) Tj
-222 -11.25 TD 0.0176 Tc 3.7324 Tw (Rousseau D, Hayes) Tj
78.75 0 TD 0.003 Tc 0 Tw (-) Tj
3 0 TD 0.0492 Tc 2.9508 Tw (Roth B, 1996) Tj
54.75 0 TD 0.0467 Tc 2.2033 Tw ( "Personality in Synthetic ) Tj
-126.75 -11.25 TD 0.0101 Tc -0.0101 Tw (Agents", ) Tj
33.75 0 TD 0 Tc 0 Tw ( ) Tj
-43.5 -11.25 TD 0.0176 Tc 1.1074 Tw (Rousseau D, Hayes) Tj
73.5 0 TD 0.003 Tc 0 Tw (-) Tj
3 0 TD 0.0292 Tc 0.7208 Tw (Roth B, 1997 "Interacting with Personality) Tj
159 0 TD 0.003 Tc 0 Tw (-) Tj
-225.75 -11.25 TD -0.0411 Tc 0.0411 Tw (Rich Characters", ) Tj
65.25 0 TD 0 Tc 0 Tw ( ) Tj
-75 -11.25 TD -0.1067 Tc 3.8567 Tw (Sengers P, 1998a) Tj
0 Tc 0 Tw ( ) Tj
74.25 0 TD /F2 9 Tf
-0.1882 Tc (Anti) Tj
14.25 0 TD 0.003 Tc (-) Tj
3 0 TD -0.0832 Tc 3.5332 Tw (Boxology: Agent Design in Cultural) Tj
0 Tc 0 Tw ( ) Tj
-81.75 -11.25 TD -0.1427 Tc (Context) Tj
27 0 TD /F1 9 Tf
-0.0208 Tc 0.0208 Tw (, Carnegie Mellon University, Pittsburgh) Tj
147 0 TD 0 Tc 0 Tw ( ) Tj
-183.75 -11.25 TD -0.0527 Tc 2.4277 Tw (Sengers P, 1998b "Do the Thing Ri) Tj
140.25 0 TD -0.0109 Tc 1.8109 Tw (ght: An Architecture for ) Tj
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