Steve Hanks, Stuart Russell, and Michael P.Wellman, editors. AAAI Spring Symposium on Decision-Theoretic Planning. AAAI Press, March1994.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....performs a forward search in a space of world states, which is somewhat untraditional in planning 7 . However, the current trend in planning seems to put the stress on the need for more powerful action formalisms [22, 15] for more elaborate preference criteria than the minimal plan length one [14], and work on planning under uncertainty, e.g. 18] seems to go beyond the possibly versus necessary difference between plans and diagnoses, thereby making diagnosis and planning search spaces similar. Future work will more carefully explore the possibility of using these new planning ....

S. Hanks, S. Russel, and M.P. Wellman, editors. Proc. AAAI Spring Symposium on Decision-Theoretic Planning. AAAI Press, 1994.

....in such systems is implicit in the searchcontrol heuristics used by the planner during the process of means end reasoning. More recently, there have been efforts to integrate explicit decision theoretic deliberation processes with traditional AI planning generation [Haddawy and Suwandi 1994,Hanks et al. 1994] but no single solution has yet been agreed upon. IRMA provides one candidate architecture for combining these two reasoning tasks. In sum, previous theorizing suggested to us that agents in dynamic environments may profit from committing to their plans, and tending to filter from further ....

Steve Hanks, Stuart Russell, and editors Michael Wellman. AAAI Spring Symposium on Decision-Theoretic Planning. AAAI Press, Menlo Park, CA, 1994.

....widely accepted in the AI planning community that planning schemes which strive to solve realistic problems must be able to model uncertainty as well as tradeoffs among goals and the resources consumed in achieving goals. This position has given rise to the decision theoretic planning paradigm [8]. In the framework of decision theoretic planning, uncertainty in the state of the world and in the effects of actions are represented with probabilities and the planner s goals, as well as tradeoffs among them, are represented with a utility function over outcomes. Given this representation, the ....

....; E ij )jj = 1; 2; Delta Delta Delta ; i k i ; I ij 2 I; E ij : 2 Omega 2 Omega g. We define 1. for b 2 c i ; exec(a; b) M ib ) where for A Omega M ib (A) I ij if A = E ij (b) j = 1; 2; Delta Delta Delta ; i k i 0 otherwise (3) Mpre . 8 ton deli[0] 0 present=0 fuel[0] [8, 10] ton[0] 10, 20] 2 ton deli[0] 0 present=0 fuel[0] 5, 6] ton[0] 10, 20] Deliver fuel = 7 .7 present=present 10 ton deli = 8 ton fuel=fuel 5 ton=0 .3 present=present 30 ton deli = ton fuel=fuel 6 ton=0 fuel 7 no effect Mpost .8 .7 ton deli[0] 0 present=10 fuel[0] 8, 10] ....

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S. Hanks, S. Russell, and M. Wellman, editors. AAAI Spring Symposium on Decision-Theoretic Planning, Stanford, 1994.

....widely accepted in the AI planning community that planning schemes which strive to solve realistic problems must be able to model uncertainty as well as tradeoffs among goals and the resources consumed in achieving goals. This position has given rise to the decision theoretic planning paradigm [7]. In the framework of decision theoretic planning, uncertainty in the state of the world and in the effects of actions are represented with probabilities and the planner s goals, as well as tradeoffs among them, are represented with a utility function over outcomes. Given this representation, the ....

S. Hanks, S. Russell, and M. Wellman, editors. AAAI Spring Symposium on Decision-Theoretic Planning, Stanford, 1994.

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Steve Hanks, Stuart Russell, and Michael P.Wellman, editors. AAAI Spring Symposium on Decision-Theoretic Planning. AAAI Press, March1994.

....for these principles, and thus our challenge is the development of a computational version of this theory, leading to representations and reasoning strategies combining computational plausibility with decision theoretic accountability. The name for this enterprise is decision theoretic planning [13, 31]. Just as decision theory is an appropriate abstraction for single agent behavior, economics can provide a framework for decentralization of decision making across rational agents. The key idea is that agent rationality makes it more convenient to design systems built of agents. Why should this be ....

....and employing fee structures that impose penalties on publishers for accesses that are not followed up by the users. Despite the centrality of decision theoretic rationality in our view of computational economies, at present we have little to say (beyond ideas in the current literature [13, 17]) about how to make economic agents rational in the decision theoretic sense. The reason is that there is no difference in the problem of achieving computational rationality in this context compared to any other context. That is, designing rational agents is the general AI problem, and we are ....

Steve Hanks, Stuart Russell, and Michael P. Wellman, editors. AAAI Spring Symposium on Decision-Theoretic Planning. AAAI Press, March 1994.

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