We study logical properties that concern the preservation of futuredirected obligations that have not been fulfilled yet. Our starting point is a product of temporal and deontic ...
It is known that the complexity of the reinforcement learning algorithms, such as Q-learning, may be exponential in the number of environment’s states. It was shown, however, th...
Models of agent-environment interaction that use predictive state representations (PSRs) have mainly focused on the case of discrete observations and actions. The theory of discre...
Interactions between agents in an open system such as the Internet require a significant degree of flexibility. A crucial aspect of the development of such methods is the notion o...
In many settings, agents need to identify competent partners to assist them in accomplishing tasks. Direct experience may not provide sufficient data to learn the competence of ot...