356 research outputs found
cc-Golog: Towards More Realistic Logic-Based Robot Controllers
High-level robot controllers in realistic domains typically deal with
processes which operate concurrently, change the world continuously, and where
the execution of actions is event-driven as in ``charge the batteries as soon
as the voltage level is low''. While non-logic-based robot control languages
are well suited to express such scenarios, they fare poorly when it comes to
projecting, in a conspicuous way, how the world evolves when actions are
executed. On the other hand, a logic-based control language like \congolog,
based on the situation calculus, is well-suited for the latter. However, it has
problems expressing event-driven behavior. In this paper, we show how these
problems can be overcome by first extending the situation calculus to support
continuous change and event-driven behavior and then presenting \ccgolog, a
variant of \congolog which is based on the extended situation calculus. One
benefit of \ccgolog is that it narrows the gap in expressiveness compared to
non-logic-based control languages while preserving a semantically well-founded
projection mechanism
Constraint integration and violation handling for BPEL processes
Autonomic, i.e. dynamic and fault-tolerant Web service composition is a requirement resulting from recent developments such as on-demand services. In the context of planning-based service composition, multi-agent planning and dynamic error handling are still unresolved problems. Recently, business rule and constraint management has been looked at for enterprise SOA to add business flexibility. This paper proposes a constraint integration and violation handling technique for dynamic service composition. Higher degrees of reliability and fault-tolerance, but also performance for autonomously composed WS-BPEL processes are the objectives
Logic-Based Specification Languages for Intelligent Software Agents
The research field of Agent-Oriented Software Engineering (AOSE) aims to find
abstractions, languages, methodologies and toolkits for modeling, verifying,
validating and prototyping complex applications conceptualized as Multiagent
Systems (MASs). A very lively research sub-field studies how formal methods can
be used for AOSE. This paper presents a detailed survey of six logic-based
executable agent specification languages that have been chosen for their
potential to be integrated in our ARPEGGIO project, an open framework for
specifying and prototyping a MAS. The six languages are ConGoLog, Agent-0, the
IMPACT agent programming language, DyLog, Concurrent METATEM and Ehhf. For each
executable language, the logic foundations are described and an example of use
is shown. A comparison of the six languages and a survey of similar approaches
complete the paper, together with considerations of the advantages of using
logic-based languages in MAS modeling and prototyping.Comment: 67 pages, 1 table, 1 figure. Accepted for publication by the Journal
"Theory and Practice of Logic Programming", volume 4, Maurice Bruynooghe
Editor-in-Chie
Artificial Intelligence and Systems Theory: Applied to Cooperative Robots
This paper describes an approach to the design of a population of cooperative
robots based on concepts borrowed from Systems Theory and Artificial
Intelligence. The research has been developed under the SocRob project, carried
out by the Intelligent Systems Laboratory at the Institute for Systems and
Robotics - Instituto Superior Tecnico (ISR/IST) in Lisbon. The acronym of the
project stands both for "Society of Robots" and "Soccer Robots", the case study
where we are testing our population of robots. Designing soccer robots is a
very challenging problem, where the robots must act not only to shoot a ball
towards the goal, but also to detect and avoid static (walls, stopped robots)
and dynamic (moving robots) obstacles. Furthermore, they must cooperate to
defeat an opposing team. Our past and current research in soccer robotics
includes cooperative sensor fusion for world modeling, object recognition and
tracking, robot navigation, multi-robot distributed task planning and
coordination, including cooperative reinforcement learning in cooperative and
adversarial environments, and behavior-based architectures for real time task
execution of cooperating robot teams
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