In this paper, we address the tradeo between exploration and exploitation for agents which need to learn more about the structure of their environment in order to perform more e e...
Shlomo Argamon-Engelson, Sarit Kraus, Sigalit Sina
This paper addresses the logical foundations of goal-regression planning in autonomous rational agents. It focuses mainly on three problems. The first is that goals and subgoals w...
Task execution in multi-agent environments may require cooperation among agents. Given a set of agents and a set of tasks which they have to satisfy, we consider situations where ...
Reinforcement Learning (RL) is the study of programs that improve their performance by receiving rewards and punishments from the environment. Most RL methods optimize the discoun...
In formal approaches to commonsense reasoning about actions. the Ramification Problem denotes the problem of handling indirect effects which implicitly derive from so-called state...