In several information retrieval (IR) systems there is a possibility for user feedback. Many machine learning methods have been proposed that learn from the feedback information in...
This paper describes an algorithm, called CQ-learning, which learns to adapt the state representation for multi-agent systems in order to coordinate with other agents. We propose ...
Learning Bayesian networks from data is an N-P hard problem with important practical applications. Several researchers have designed algorithms to overcome the computational comple...
Context-sensitive graph grammar construction tools have been used to develop and study interesting languages. However, the high dimensionality of graph grammars result in costly e...
Using information from failures to guide subsequent search is an important technique for solving combinatorial problems in domains such as boolean satisfiability (SAT) and constr...