Boolean linear programs (BLPs) are ubiquitous in AI. Satisfiability testing, planning with resource constraints, and winner determination in combinatorial auctions are all example...
Dale Schuurmans, Finnegan Southey, Robert C. Holte
We are interested in semantical underpinnings for existing approaches to preference handling in extended logic programming (within the framework of answer set programming). As a s...
From as early as 6 months of age, human children distinguish between motion patterns generated by animate objects from patterns generated by moving inanimate objects, even when th...
Combinatorial auctions where bidders can bid on bundles of items can lead to more economical allocations, but determining the winners is NP-complete and inapproximable. We present...
Tuomas Sandholm, Subhash Suri, Andrew Gilpin, Davi...
Market mechanisms play a central role in AI as a coordination tool in multiagent systems and as an application area for algorithm design. Mechanisms where buyers are directly clea...
For many supervised learning tasks it is very costly to produce training data with class labels. Active learning acquires data incrementally, at each stage using the model learned...
This paper develops a new paradigm for relational learning which allows for the representation and learning of relational information using propositional means. This paradigm sugg...
This paper describes a method for structuring a robot motor learning task. By designing a suitably parameterized policy, we show that a simple search algorithm, along with biologi...