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Found 8 papers, 0 papers with code
Using Non-Stationary Bandits for Learning in Repeated Cournot Games with Non-Stationary Demand
We found that using our proposed method, agents are able to swiftly change their course of action according to the changes in demand, and they also engage in collusive behavior in many simulations.
Multi-agent Reinforcement Learning for Decentralized Stable Matching
Along with conventional stable matching case where agents have strictly ordered preferences, we check the applicability of our approach for stable matching with incomplete lists and ties.
The Complexity of Campaigning
In "The Logic of Campaigning", Dean and Parikh consider a candidate making campaign statements to appeal to the voters.
Ethical Considerations in Artificial Intelligence Courses
The recent surge in interest in ethics in artificial intelligence may leave many educators wondering how to address moral, ethical, and philosophical issues in their AI courses.
Topological Value Iteration Algorithms
Value iteration is a powerful yet inefficient algorithm for Markov decision processes (MDPs) because it puts the majority of its effort into backing up the entire state space, which turns out to be unnecessary in many cases.
The Computational Complexity of Dominance and Consistency in CP-Nets
In our main results, we show here that both dominance and consistency for general CP-nets are PSPACE-complete.
Approximation of Lorenz-Optimal Solutions in Multiobjective Markov Decision Processes
This paper is devoted to fair optimization in Multiobjective Markov Decision Processes (MOMDPs).
Competition Adds Complexity
It is known that determinining whether a DEC-POMDP, namely, a cooperative partially observable stochastic game (POSG), has a cooperative strategy with positive expected reward is complete for NEXP.
