La VIDA: towards a motivated goal reasoning agent

IF 2 3区 计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS
Ursula Addison
{"title":"La VIDA: towards a motivated goal reasoning agent","authors":"Ursula Addison","doi":"10.1007/s10458-024-09685-2","DOIUrl":null,"url":null,"abstract":"<div><p>An autonomous agent deployed to operate over extended horizons in uncertain environments will encounter situations for which it was not designed. A class of these situations involves an invalidation of agent goals and limited guidance in establishing a new set of goals to pursue. An agent will benefit from some mechanism that will allow it to pursue new goals under these circumstances such that the goals are broadly useful in its environment and take advantage of its existing skills while aligning with societal norms. We propose augmenting a goal reasoning agent, i.e., an agent that can deliberate on and self-select its goals, with a motivation system that can be used to both constrain and motivate agent behavior. A human-like motivation system coupled with a goal-self concordant selection technique allows the approach to be framed as an optimization problem in which the agent selects goals that have high utility while simultaneously in harmony with its motivations. Over the agent’s operational lifespan its motivation system adjusts incrementally to more closely reflect the reality of its goal reasoning and goal pursuit experiences. Experiments performed with an ablation testing technique comparing the average utility of goals achieved in the presence and absence of a motivation system suggest that the motivated version of the system leads to pursuing more useful goals than the baseline.</p></div>","PeriodicalId":55586,"journal":{"name":"Autonomous Agents and Multi-Agent Systems","volume":"39 1","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Autonomous Agents and Multi-Agent Systems","FirstCategoryId":"94","ListUrlMain":"https://link.springer.com/article/10.1007/s10458-024-09685-2","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0

Abstract

An autonomous agent deployed to operate over extended horizons in uncertain environments will encounter situations for which it was not designed. A class of these situations involves an invalidation of agent goals and limited guidance in establishing a new set of goals to pursue. An agent will benefit from some mechanism that will allow it to pursue new goals under these circumstances such that the goals are broadly useful in its environment and take advantage of its existing skills while aligning with societal norms. We propose augmenting a goal reasoning agent, i.e., an agent that can deliberate on and self-select its goals, with a motivation system that can be used to both constrain and motivate agent behavior. A human-like motivation system coupled with a goal-self concordant selection technique allows the approach to be framed as an optimization problem in which the agent selects goals that have high utility while simultaneously in harmony with its motivations. Over the agent’s operational lifespan its motivation system adjusts incrementally to more closely reflect the reality of its goal reasoning and goal pursuit experiences. Experiments performed with an ablation testing technique comparing the average utility of goals achieved in the presence and absence of a motivation system suggest that the motivated version of the system leads to pursuing more useful goals than the baseline.

Abstract Image

La VIDA:走向一个有动机的目标推理代理
部署在不确定环境中进行扩展视界操作的自主代理将遇到其设计之外的情况。这类情况包括代理目标无效和在建立一组新目标时的有限指导。代理将受益于某些机制,这些机制将允许它在这些情况下追求新的目标,使这些目标在其环境中广泛有用,并利用其现有技能,同时与社会规范保持一致。我们提出用一个可以约束和激励代理行为的激励系统来增强一个目标推理代理,即一个可以考虑和自我选择目标的代理。类人动机系统与目标-自我协调选择技术相结合,使该方法被框架为一个优化问题,其中智能体选择具有高效用的目标,同时与其动机协调一致。在智能体的生命周期中,其动机系统会逐渐调整,以更紧密地反映其目标推理和目标追求经验的现实。用消融测试技术进行的实验比较了在存在和不存在激励系统的情况下实现目标的平均效用,结果表明,激励系统的版本会导致追求比基线更有用的目标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Autonomous Agents and Multi-Agent Systems
Autonomous Agents and Multi-Agent Systems 工程技术-计算机:人工智能
CiteScore
6.00
自引率
5.30%
发文量
48
审稿时长
>12 weeks
期刊介绍: This is the official journal of the International Foundation for Autonomous Agents and Multi-Agent Systems. It provides a leading forum for disseminating significant original research results in the foundations, theory, development, analysis, and applications of autonomous agents and multi-agent systems. Coverage in Autonomous Agents and Multi-Agent Systems includes, but is not limited to: Agent decision-making architectures and their evaluation, including: cognitive models; knowledge representation; logics for agency; ontological reasoning; planning (single and multi-agent); reasoning (single and multi-agent) Cooperation and teamwork, including: distributed problem solving; human-robot/agent interaction; multi-user/multi-virtual-agent interaction; coalition formation; coordination Agent communication languages, including: their semantics, pragmatics, and implementation; agent communication protocols and conversations; agent commitments; speech act theory Ontologies for agent systems, agents and the semantic web, agents and semantic web services, Grid-based systems, and service-oriented computing Agent societies and societal issues, including: artificial social systems; environments, organizations and institutions; ethical and legal issues; privacy, safety and security; trust, reliability and reputation Agent-based system development, including: agent development techniques, tools and environments; agent programming languages; agent specification or validation languages Agent-based simulation, including: emergent behavior; participatory simulation; simulation techniques, tools and environments; social simulation Agreement technologies, including: argumentation; collective decision making; judgment aggregation and belief merging; negotiation; norms Economic paradigms, including: auction and mechanism design; bargaining and negotiation; economically-motivated agents; game theory (cooperative and non-cooperative); social choice and voting Learning agents, including: computational architectures for learning agents; evolution, adaptation; multi-agent learning. Robotic agents, including: integrated perception, cognition, and action; cognitive robotics; robot planning (including action and motion planning); multi-robot systems. Virtual agents, including: agents in games and virtual environments; companion and coaching agents; modeling personality, emotions; multimodal interaction; verbal and non-verbal expressiveness Significant, novel applications of agent technology Comprehensive reviews and authoritative tutorials of research and practice in agent systems Comprehensive and authoritative reviews of books dealing with agents and multi-agent systems.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信