The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
In this paper, we explore the feasibility and performance optimization problems for real-time systems that must remain functional during an operation/mission with a fixed, initial...
ABSTRACT. We present PICPA, a new algorithm for tackling constrained continuous multiobjective problems. The algorithm combines constraint propagation techniques and evolutionary c...
Action modeling is an important skill for agents that must perform tasks in novel domains. Previous work on action modeling has focused on learning STRIPS operators in discrete, r...
Dynamic Resource-Constrained Project Scheduling Problem (DRCPSP) is a scheduling problem that works with an uncommon kind of resources: the Dynamic Resources. They increase and dec...