Representing plans under uncertainty: a logic of time, chance, and action
This is the third in a series of specialized international symposia held every two years and dedicated to presenting and discussing in depth the research results and on-going developments in robotics which have both theoretical foundations and experimental validations. There are 43 papers, from 10 countries, presented in nine titled sections.
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List of Figures 1 The temporal tree
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action attempts action is feasible action occurrence action token activity network agent assumption ATT(A ATT(A,tA attempt an action attempt the action Barcan formula concurrently conditional expected conditional probability constraints CPM algorithm Ctca Decision Theory decision-theoretic defined definition of c-prob described effects of actions event token event type example executability conditions expected utility expected value facts and events FEAS(A,tA feasibility conditions Field axioms first-order first-order logic follows framework inevitability infer interval language lower bound Miller's principle modal operators model theory MoPo nodes objective chance OCC(A occur ontology Ot<j Pelavin pi(G plan is feasible planning algorithm planning problems possible Present and past probabilistic probability axioms proof proof theory proposition ramification conditions reasoning about plans represent resource roof panels roof trusses semantics sentence shown in Fig steel crew subjective probability Suppose t-terms temporal tree Theorem true iff trying to attempt utility function world-histories