Change points are abrupt variations in time series data. Such abrupt changes may represent
transitions that occur between states. Detection of change points is useful in modelling and …

Anytime algorithms give intelligent systems the capability to trade deliberation time for
quality of results. This capability is essential for successful operation in domains such as …

The performance of a reinforcement learning algorithm can vary drastically during learning
because of exploration. Existing algorithms provide little information about the quality of their …

Coalition formation is a key topic in multiagent systems. One may prefer a coalition structure
that maximizes the sum of the values of the coalitions, but often the number of coalition …

Since its inception, artificial intelligence has relied upon a theoretical foundation centered
around perfect rationality as the desired property of intelligent systems. We argue, as others …

The long-term goal of our field is the creation and understanding of intelligence. Productive
research in AI, both practical and theoretical, benefits from a notion of intelligence that is …

This paper analyzes coalitions among self-interested agents that need to solve
combinatorial optimization problems to operate efficiently in the world. By colluding …

Various disciplines have examined the many phenomena of metacognition and have
produced numerous results, both positive and negative. I discuss some of these aspects of …

The evolutionary history of animal cognition appears to involve a few major transitions:
major changes that opened up new phylogenetic possibilities for cognition. Here, we review …

Data analysis is fundamentally an iterative process in which you issue a query, receive a
response, formulate the next query based on the response, and repeat. You usually don't …