Foundations of logic programming; (2nd extended ed.)
Foundations of logic programming; (2nd extended ed.)
Introduction to algorithms
A logic for reasoning about probabilities
Information and Computation - Selections from 1988 IEEE symposium on logic in computer science
Representing plans under uncertainty: a logic of time, chance, and action
Representing plans under uncertainty: a logic of time, chance, and action
Handbook of logic in artificial intelligence and logic programming (vol. 3)
Features and fluents (vol. 1): the representation of knowledge about dynamical systems
Features and fluents (vol. 1): the representation of knowledge about dynamical systems
Reasoning about knowledge
ProbView: a flexible probabilistic database system
ACM Transactions on Database Systems (TODS)
Heterogeneous active agents, I: semantics
Artificial Intelligence
ACM Transactions on Computational Logic (TOCL)
Artificial Intelligence
A Survey of Concurrent METATEM - the Language and its Applications
ICTL '94 Proceedings of the First International Conference on Temporal Logic
METATEM: A Framework for Programming in Temporal Logic
Stepwise Refinement of Distributed Systems, Models, Formalisms, Correctness, REX Workshop
Declarative programming for agent applications
Autonomous Agents and Multi-Agent Systems
Annals of Mathematics and Artificial Intelligence
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Situated agents in the real world need to handle the fact that events occur frequently, as well as the fact that the agent typically has uncertain knowledge about what is true in the world. The ability to reason about both time and uncertainty is therefore very important. In this paper, we develop a formal theory of agents that can reason about both time and uncertainty. The theory extends the notion of agents described in [10, 21] and proposes the notion of temporal probabilistic (or TP) agents. A formal semantics for TP-agents is proposed - this semantics is described via structures called feasible TP-status interpretations (FTPSI's). TP-agents continuously evaluate changes (in the state of the environment they are situated in) and compute appropriate FTPSI's. For a class of TP-agents called positive TP-agents, we develop a provably sound and complete procedure to compute FTPSI's.