Acting in a dynamic environment is a complex task that requires several issues to be investigated, with the aim of controlling the associated search complexity. In this paper, a l...
Planning has traditionally focused on single agent systems. Although planning domain languages have been extended to multiagent domains, solution concepts have not. Previous solut...
Michael H. Bowling, Rune M. Jensen, Manuela M. Vel...
Recent research has addressed the problem of planning in non-deterministic domains. Classical planning has also been extended to the case of goals that can express temporal proper...
Recently tremendous advances have been made in the performance of AI planning systems. However increased performance is only one of the prerequisites for bringing planning into th...
In the last decade, there has been several studies on the computational complexity of planning. These studies normally assume that the goal of planning is to make a certain fluent...
This paper presents a novel idea, which combines Planning, Machine Learning and Knowledge-Based techniques. It is concerned with the development of an adaptive planning system tha...
Dimitris Vrakas, Grigorios Tsoumakas, Nick Bassili...
We present a framework for coordinating autonomous planning agents. Together, these agents have to achieve a set of interdependent (elementary) tasks. Each of the agents receives a...
Temporally extended goals (TEGs) refer to properties that must hold over intermediate and/or final states of a plan. Current planners for TEGs prune the search space during planni...
There is a great interest in the planning community to apply all developments already achieved in the area to real applications. Such scenario makes the community focus on Knowled...