Learning, planning, and representing knowledge in large state t multiple levels of temporal abstraction are key, long-standing challenges for building flexible autonomous agents. ...
In this paper, we propose a Quantified Distributed Constraint Optimization problem (QDCOP) that extends the framework of Distributed Constraint Optimization problems (DCOPs). DCOP...
Evolutionary algorithms (EAs) are increasingly being applied to solve real-parameter optimization problems due to their flexibility in handling complexities such as non-convexity,...
Rupesh Tulshyan, Ramnik Arora, Kalyanmoy Deb, Joyd...
We introduce the Scanalyzer planning domain, a domain for classical planning which models the problem of automatic greenhouse logistic management. At its mathematical core, the Sc...
Discriminative subgraphs are widely used to define the feature space for graph classification in large graph databases. Several scalable approaches have been proposed to mine disc...