In many real-world situations, a planner is part of an integrated problem-solving environment and must operate concurrently with other planners and special purpose inference engines. Unlike the traditional AI planners, planners operating in such concurrent environments have to contend with an evolving problem specification, and should be able to interact and coordinate with the other modules on a continual basis. This in turn poses several critical requirements on the planning methodology
Automated, domain-independent planning is a research area within Artificial Intelligence that is use...
Abstract: Realistic planning systems must allow users and computer systems to co-operate and work to...
In this work we present a novel approach to solving concurrent multiagent planning problems in which...
Tutor: Anders JonssonTreball fi de màster de: Master in Intelligent Interactive SystemsIn this work,...
This document is a first year PhD report describing an emergent research line based on the efforts o...
AbstractThis paper presents an integrated view of a wide range of planning systems derived from diff...
Comunicació presentada al 6th Workshop on Distributed and Multi-Agent Planning (DMAP 2018), celebrat...
This paper investigates how centralised, cooperative, multi-agent planning problems with concurrent ...
The ability of temporal planners to find concurrent plans can potentially be exploited in multiagent...
In realtime planning domains, such as service robot control, an agent receives a task and must minim...
Comunicació presentada al 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovativ...
Comunicació presentada al 6th Workshop on Distributed and Multi-Agent Planning (DMAP 2018), celebrat...
Automated planning is a central area of artificial intelli-gence, involving the design of languages ...
Intelligent problem solving requires the ability to select actions autonomously from a specific stat...
Automated, domain-independent planning is a research area within Artificial Intelligence that is use...
Automated, domain-independent planning is a research area within Artificial Intelligence that is use...
Abstract: Realistic planning systems must allow users and computer systems to co-operate and work to...
In this work we present a novel approach to solving concurrent multiagent planning problems in which...
Tutor: Anders JonssonTreball fi de màster de: Master in Intelligent Interactive SystemsIn this work,...
This document is a first year PhD report describing an emergent research line based on the efforts o...
AbstractThis paper presents an integrated view of a wide range of planning systems derived from diff...
Comunicació presentada al 6th Workshop on Distributed and Multi-Agent Planning (DMAP 2018), celebrat...
This paper investigates how centralised, cooperative, multi-agent planning problems with concurrent ...
The ability of temporal planners to find concurrent plans can potentially be exploited in multiagent...
In realtime planning domains, such as service robot control, an agent receives a task and must minim...
Comunicació presentada al 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovativ...
Comunicació presentada al 6th Workshop on Distributed and Multi-Agent Planning (DMAP 2018), celebrat...
Automated planning is a central area of artificial intelli-gence, involving the design of languages ...
Intelligent problem solving requires the ability to select actions autonomously from a specific stat...
Automated, domain-independent planning is a research area within Artificial Intelligence that is use...
Automated, domain-independent planning is a research area within Artificial Intelligence that is use...
Abstract: Realistic planning systems must allow users and computer systems to co-operate and work to...
In this work we present a novel approach to solving concurrent multiagent planning problems in which...