Formal theories of knowledge in AI and robotics
New Generation Computing
Knowledge representation and reasoning
Annual review of computer science vol. 1, 1986
Reasoning about knowledge: an overview
Proceedings of the 1986 Conference on Theoretical aspects of reasoning about knowledge
Readings in nonmonotonic reasoning
Readings in nonmonotonic reasoning
Constructive belief and rational representation
Computational Intelligence
Knowledge and common knowledge in a distributed environment
Journal of the ACM (JACM)
Impediments to Universal preference-based default theories
Proceedings of the first international conference on Principles of knowledge representation and reasoning
Finding MAPs for belief networks is NP-hard
Artificial Intelligence
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
A neo2 Bayesian foundation of the maxmin value for two-person zero-sum games
International Journal of Game Theory
Reasoning about knowledge
Modeling agents as qualitative decision makers
Artificial Intelligence - Special issue on economic principles of multi-agent systems
Online computation and competitive analysis
Online computation and competitive analysis
Belief Revision
ICALP '89 Proceedings of the 16th International Colloquium on Automata, Languages and Programming
A knowledge-based framework for belief change part I: foundations
TARK '94 Proceedings of the 5th conference on Theoretical aspects of reasoning about knowledge
On decision theoretic foundations for defaults
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Generalized qualitative probability: savage revisited
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Qualitative decision theory: from savage's axioms to nonmonotonic reasoning
Journal of the ACM (JACM)
Game Theory and Artificial Intelligence
Selected papers from the UKMAS Workshop on Foundations and Applications of Multi-Agent Systems
On preference-based search in state space graphs
Eighteenth national conference on Artificial intelligence
Artificial Intelligence - Special issue: Fuzzy set and possibility theory-based methods in artificial intelligence
Decision making for symbolic probability
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Decision making on the sole basis of statistical likelihood
Artificial Intelligence
Research note: A representation theorem for minmax regret policies
Artificial Intelligence
Making Discrete Sugeno Integrals More Discriminant
International Journal of Approximate Reasoning
On the qualitative comparison of decisions having positive and negative features
Journal of Artificial Intelligence Research
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Decision making on the sole basis of statistical likelihood
Artificial Intelligence
A general framework for explaining the results of a multi-attribute preference model
Artificial Intelligence
Vector-Value Markov Decision Process for multi-objective stochastic path planning
International Journal of Hybrid Intelligent Systems
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The need for computationally efficient decision-making techniques together with the desire to simplify the processes of knowledge acquisition and agent specification have led various researchers in artificial intelligence to examine qualitative decision tools. However, the adequacy of such tools is not clear. This paper investigates the foundations of maximin, minmax regret, and competitive ratio, three central qualitative decision criteria, by characterizing those behaviors that could result from their use. This characterizaton provides two important insights: (1)under what conditions can we employ an agent model based on these basic qualitative decision criteria, and (2) how “rational” are these decision procedures. For the competitive ratio criterion in particular, this latter issue is of central importance to our understanding of current work on on-line algorithms. Our main result is a constructive representation theorem that uses two choice axioms to characterize maximin, minmax regret, and competitive ratio.