Cross-paradigm analysis of autonomous agent architecture (original) (raw)
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We present a general architecture for autonomous artificial agents that allows them to cope with the occurrence of internal and external stimuli simultaneously to their ongoing cognitive activities. This new architecture develops general proposals by Simon [1967] and Sloman [1987; 1995] particularized to the model described in [Botelho and Coelho 1995]. We relate the dispute between the primacy of affect and the primacy of cognition to the proposed architecture. Within the mentioned architecture we describe a new mechanism based on emotion and attribution, for controlling attention shift. Automatic as opposed to thoughtful and deliberate decision is a fundamental asset of our approach. Such automaticity is only possible because it draws on properties of the SALT model of memory [Botelho and Coelho 1995]. We relate our proposal to previous work on attention shift [Beaudoin and Sloman 1993], dynamic context-dependent change [Maes 1989] and commitment policies [Pollack and Ringuette 1990] and [Kinny and Georgeff 1991], and show how these former mechanisms may be defined within the proposed architecture. 1-Introduction Attention shift refers to what happens when some agent stops attending to its current thinking and attends to some external or internal event or object.
2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA), 2016
Due to their increasing complexity, the implementation of automation systems faces more challenges. Cognitive architectures have been designed to deal exactly with that. The purpose of a cognitive architecture is to find an action to every possible sensor data to move the system closer to a defined goal. The method is to utilize stored knowledge to reason about the best solution. The challenge for the implementation of such an architecture is to manage the overwhelming complexity of functionality and data. This paper presents the Agent-based Cognitive Architecture (ACONA) Framework, which aims at providing a general infrastructure, allowing the implementation of various cognitive architectures. It considers the encapsulation of functionality and provides a flexible composition of building blocks by applying a multi-agent approach.
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Architectures and idioms: Making progress in agent design
Intelligent Agents VII Agent Theories Architectures and …, 2001
This chapter addresses the problem of producing and maintaining progress in agent design. New architectures often hold important insights into the problems of designing intelligence. Unfortunately, these ideas can be difficult to harness, because on established projects switching between architectures and languages carries high cost. We propose a solution whereby the research community takes responsibility for re-expressing innovations as idioms or extensions of one or more standard architectures. We describe the process and provide an example -the concept of a Basic Reactive Plan. This idiom occurs in several influential agent architectures, yet in others is difficult to express. We also discuss our proposal's relation to the the roles of architectures, methodologies and toolkits in the design of agents.
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Many modern artificial intelligence (AI) systems, including both real physical robots and animat-based models are structured using intelligent agents. A key challenge for building large and complex AI systems is to manage the agent interactions in an appropriate architecture that supports complexity in a scalable and hierarchical manner. In this article we review various agent architectures for both physical and simulated robot systems, and show how appropriate agent communications protocols can be developed to support artificially intelligent systems based on communities of interacting agents. As well as reviewing some of the architectures and supporting software tools and technologies, we present our own ideas for a software architecture for managing intelligent agents. We emphasise the importance of being able to incrementally augment the set of agents as new ideas are developed. We describe how key activities such as agent navigation in physical and simulated spaces; agent communication; world state management and sensory integration all need to be managed in an appropriate framework to support individual agents that will take responsibility for tasks and goals.
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Robotic agents consist of various compositions of properties that are found in their mechatronics, behavioural and cognitive architectures. Common properties of each architecture type serve as criteria for assessing the degree of intelligence of most embodied agent models. Although embodied intelligence has long been accepted for robotic agents, the literature is short on combined evaluations that discuss all properties of all architecture types in one framework. Here we provide a review of existing taxonomies for each type of architecture and attempt to combine them all in a single taxonomy for robotic agents.