The agent architecture InteRRaP : concept and application

One of the basic questions of research in Distributed Artificial Intelligence (DAI) is how agents have to be structured and organized, and what functionalities they need in order to be able to act and to interact in a dynamic environment. To cope with this question is the purpose of models and architectures for autonomous and intelligent agents. In the first part of this report, InteRRaP, an agent architecture for multi-agent systems is presented. The basic idea is to combine the use of patterns of behaviour with planning facilities in order to be able to exploit the advantages both of the reactive, behaviour-based and of the deliberate, plan-based paradigm. Patterns of behaviour allow an agent to react flexibly to changes in its environment. What is considered necessary for the performance of more sophisticated tasks is the ability of devising plans deliberately. A further important feature of the model is that it explicitly represents knowledge and strategies for cooperation. This makes it suitable for describing high-level interaction among autonomous agents. In the second part of the report, the loading-dock domain is presented, which has been the first application the InteRRaP agent model has been tested with. An automated loading-dock is described where the agent society consists of forklifts which have to load and unload trucks in a shared, dynamic environment

Cooperative transportation scheduling : an application domain for DAI

A multiagent approach to designing the transportation domain is presented. The MARS system is described which models cooperative order scheduling within a society of shipping companies. We argue why Distributed Artificial Intelligence (DAI) offers suitable tools to deal with the hard problems in this domain. We present three important instances for DAI techniques that proved useful in the transportation application: cooperation among the agents, task decomposition and task allocation, and decentralised planning. An extension of the contract net protocol for task decomposition and task allocation is presented; we show that it can be used to obtain good initial solutions for complex resource allocation problems. By introducing global information based upon auction protocols, this initial solution can be improved significantly. We demonstrate that the auction mechanism used for schedule optimisation can also be used for implementing dynamic replanning. Experimental results are provided evaluating the performance of different scheduling strategies

Unifying control in a layered agent architecture

In this paper, we set up a unifying perspective of the individual control layers of the architecture InteRRaP for autonomous interacting agents. InteRRaP is a pragmatic approach to designing complex dynamic agent societies, e.g. for robotics Müller & Pischel and cooperative scheduling applications Fischer et al.94. It is based on three general functions describing how the actions an agent commits to are derived from its perception and from its mental model: belief revision and abstraction, situation recognition and goal activation, and planning and scheduling. It is argued that each InteRRaP control layer - the behaviour-based layer, the local planning layer, and the cooperative planning layer - can be described by a combination of different instantiations of these control functions. The basic structure of a control layer is defined. The individual functions and their implementation in the different layers are outlined. We demonstrate various options for the design of interacting agents within this framework by means of an interacting robots application. The performance of different agent types in a multiagent environment is empirically evaluated by a series of experiments

On the representation of temporal knowledge

The growing interest in an adequate modelling of time in Artificial Intelligence has given rise to the research discipline of Temporal Reasoning (TR). Due to different views, different approaches towards TR such as PL1, modal logics or Allen\u27s intervall logic have been investigated. It was realized at an early stage that each of this approaches has some strong points whereas it suffers from certain drawbacks. Thus recently, a number of research activities have emerged aiming at a combination of the classical paradigms for representing time. In the first part of this paper, we present an overview of the most important approaches to the integration of temporal knowledge into logic programming. In the second part, we present the CRONOLOG temporal logic programming language which has been developed to cover the quintessence of the approaches presented before. The third part of the paper describes TRAM, which it is an extension of CRONOLOG to a temporal knowledge representation system. Using TRAM it is possible to represent knowledge depending on time and to reason about this knowledge. TRAM has been conceptually based on a combination of modal logics with Allen\u27s interval logic. We present the Extended Modal Logics (EML) which establishes the theoretical framework for TRAM. We define an operational semantics and a horizontal compilation scheme for TRAM

Unifying control in a layered agent architecture

In this paper, we set up a unifying perspective of the individual control layers of the architecture InteRRaP for autonomous interacting agents. InteRRaP is a pragmatic approach to designing complex dynamic agent societies, e.g. for robotics Müller & Pischel and cooperative scheduling applications Fischer et al.94. It is based on three general functions describing how the actions an agent commits to are derived from its perception and from its mental model: belief revision and abstraction, situation recognition and goal activation, and planning and scheduling. It is argued that each InteRRaP control layer - the behaviour-based layer, the local planning layer, and the cooperative planning layer - can be described by a combination of different instantiations of these control functions. The basic structure of a control layer is defined. The individual functions and their implementation in the different layers are outlined. We demonstrate various options for the design of interacting agents within this framework by means of an interacting robots application. The performance of different agent types in a multiagent environment is empirically evaluated by a series of experiments

An Agent Specification Language

This paper describes ALADIN, a language for the design of agents according to the INTERRAP agent architecture. INTERRAP is a layered architecture consisting of three control layers: a behaviourbased layer, a local planning layer, and a cooperative planning layer. The basic structure of the architecture is described, and the language constructs and the underlying execution mechanism are presented. The language constructs provided by ALADIN support the implementation of agent capabilities located at different layers of the NTERRAP control hierarchy: the structure of patterns of behaviour, single-agent plans, joint plans, and negotiation protocols is defined. ALADIN has been implemented based on the Oz language. The paper discusses some aspects of the implementation, and of how the features offered by Oz support the design of a higher-level agent language

Unifying control in a layered agent architecture. IJCAI95, Agent Theory, Architecture and language workshop, pp 240-252 Ingalls R.G

In this paper, we set up a unifying perspective of the individual control layers of the architecture InteRRaP for autonomous interacting agents. InteRRaP is a pragmatic approach to designing complex dynamic agent societies, e.g. for robotics [Muller & Pischel 94a] and cooperative scheduling applications [Fischer et al. 94]. It is based on three general functions describing how the actions an agent commits to are derived from its perception and from its mental model: belief revision and abstraction, situation recognition and goal activation, and planning and scheduling. It is argued that each InteRRaP control layer | the behaviour-based layer, the local planning layer, and the cooperative planning layer | can be described by a combination of di erent instantiations of these control functions. The basic structure of a control layer is de ned. The individual functions and their implementation in the di erent layers are outlined. We demonstrate various options for the design of interacting agents within this framework by means of an interacting robots application. The performance of di erent agent types in a multiagent environment is empirically evaluated by a series of experiments

A model for cooperative transportation scheduling

The Mars system is described which models cooperative scheduling within a society of shipping companies as a multiagent system. Emphasis is placed on the functionality of the system as a whole--- the solution of the global scheduling problem emerges from local decision-making and problem-solving strategies. An extension of the contract net protocol is presented; we show that it can be used to obtain good initial solutions for complex resource allocation problems. By introducing global information based upon auction protocols, this initial solution can be improved significantly. Experimental results are provided evaluating the performance of different cooperative scheduling strategies. Although the concepts for resource scheduling are presented solely for the transportation domain, their abstraction is useful for a broad variety of resource allocation problems. The Mars system solves the dynamic scheduling problem where no complete specification of the problem is available a priori; thus, it is designed as an on-line system based upon anytime algorithms

Web Economics: A Case for Agent-Based Digital Libraries

We advocate agent-based digital libraries as a key technology for solving some of the most important problems associated with the internet today. In particular, the aims of this paper are six-fold: to introduce the state of the art in internet-based information systems and in particular, the World-Wide Web (WWW); to detail some problems associated with the internet/WWW as it currently stands; to discuss the requirements for tools to overcome these problems; to motivate the idea of a digital library (DL) as the kind of system that will meet these requirements; to justify the claim that an appropriate way to build such digital libraries is as an agentbased information economy; and finally, to introduce ZUNODL (Zuno Digital Library), a forthcoming commercial framework for building digital libraries as agent-based information economies