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ATAL
2010
Springer
15 years 7 months ago
Learning context conditions for BDI plan selection
An important drawback to the popular Belief, Desire, and Intentions (BDI) paradigm is that such systems include no element of learning from experience. In particular, the so-calle...
Dhirendra Singh, Sebastian Sardiña, Lin Pad...
ML
2006
ACM
113views Machine Learning» more  ML 2006»
15 years 6 months ago
Learning to bid in bridge
Bridge bidding is considered to be one of the most difficult problems for game-playing programs. It involves four agents rather than two, including a cooperative agent. In additio...
Asaf Amit, Shaul Markovitch
TSMC
2008
146views more  TSMC 2008»
15 years 6 months ago
Decentralized Learning in Markov Games
Learning Automata (LA) were recently shown to be valuable tools for designing Multi-Agent Reinforcement Learning algorithms. One of the principal contributions of LA theory is tha...
Peter Vrancx, Katja Verbeeck, Ann Nowé
TKDE
2010
164views more  TKDE 2010»
15 years 5 months ago
Defeasible Contextual Reasoning with Arguments in Ambient Intelligence
Abstract—The imperfect nature of context in Ambient Intelligence environments and the special characteristics of the entities that possess and share the available context informa...
Antonis Bikakis, Grigoris Antoniou
AI
2011
Springer
15 years 1 months ago
A logic for reasoning about counterfactual emotions
The aim of this work is to propose a logical framework for the specification of cognitive emotions that are based on counterfactual reasoning about agents’ choices. An example ...
Emiliano Lorini, François Schwarzentruber