We present dcl-pc: a dynamic logic of delegation and cooperation. The logical foundation of dcl-pc is cl-pc, a logic for reasoning about cooperation in which the powers of agents ...
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Most data-mining techniques seek a single model that optimizes an objective function with respect to the data. In many real-world applications several models will equally optimize...
This paper details a research methodology that emerged during an inquiry into game design aimed at promoting conceptual learning in physics. The methodology, Research as DesignDes...
Abstract. Learning from multi-relational domains has gained increasing attention over the past few years. Inductive logic programming (ILP) systems, which often rely on hill-climbi...