Artificial Intelligence - Special issue on knowledge representation
Intention reconsideration in complex environments
AGENTS '00 Proceedings of the fourth international conference on Autonomous agents
Principles of intention reconsideration
Proceedings of the fifth international conference on Autonomous agents
Autonomous Agents and Multi-Agent Systems
Reasoning about Intentions in Uncertain Domains
ECSQARU '01 Proceedings of the 6th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Decision-Theoretic, High-Level Agent Programming in the Situation Calculus
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Intention Reconsideration Reconsidered
ATAL '98 Proceedings of the 5th International Workshop on Intelligent Agents V, Agent Theories, Architectures, and Languages
Dynamic Programming
Commitment and effectiveness of situated agents
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 1
Planning and acting in partially observable stochastic domains
Artificial Intelligence
On the relationship between MDPs and the BDI architecture
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
A hybrid approach to multi-agent decision-making
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
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Decision theoretic planning in ai by means of solving Partially Observable Markov decision processes (pomdps) has been shown to be both powerful and versatile. However, such approaches are computationally hard and, from a design stance, are not necessarily intuitive for conceptualising many problems. We propose a novel method for solving pomdps, which provides a designer with a more intuitive means of specifying pomdp planning problems. In particular, we investigate the relationship between pomdp planning theory and belief-desire-intention (bdi) agent theory. The idea is to view a bdi agent as a specification of an pomdp problem. This view is to be supported by a correspondence between an pomdp problem and a bdi agent. In this paper, we outline such a correspondence between pomdp and bdi by explaining how to specify one in terms of the other. Additionally, we illustrate the significance of a correspondence by showing empirically that it yields satisfying results in complex domains.