{"title":"Human-inspired goal reasoning implementations: A survey","authors":"Ursula Addison","doi":"10.1016/j.cogsys.2023.101181","DOIUrl":null,"url":null,"abstract":"<div><p>Goal reasoning is the ability of an artificial system to reason over its goals; it can identify, manage, plan, and execute its goals. In complex environments where requirements could change often, goal reasoning functionality is essential. Goal reasoning agents may rely on a motivation system to guide the goal reasoning process; we refer to such agents as motivated agents. Motivated agents can be explicitly or implicitly motivated by external or internal motivations. While the bulk of goal reasoning work has focused on agents that have implicit external motivations, internal motivations may offer some unique benefits to goal reasoning. As artificial internal motivations have a natural analogue to the human motivation system, this work investigates recent advances in motivated agents, where motivations are modeled on the human integrated-self. In this survey, we review those goal reasoning systems whose meta-reasoning and other goal reasoning subprocesses are at least in part intrinsic or identified, i.e., arising from idiosyncratic factors such as identity, a value system, emotions, experiences and so forth. For each system surveyed we evaluate its goal reasoning processes according to an analysis framework. We use our findings to draw conclusions about the potential benefits the three self-system categories: motives, mental simulation, and emotion bring to the goal reasoning paradigm.</p></div>","PeriodicalId":55242,"journal":{"name":"Cognitive Systems Research","volume":"83 ","pages":"Article 101181"},"PeriodicalIF":2.1000,"publicationDate":"2023-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cognitive Systems Research","FirstCategoryId":"102","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1389041723001158","RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Goal reasoning is the ability of an artificial system to reason over its goals; it can identify, manage, plan, and execute its goals. In complex environments where requirements could change often, goal reasoning functionality is essential. Goal reasoning agents may rely on a motivation system to guide the goal reasoning process; we refer to such agents as motivated agents. Motivated agents can be explicitly or implicitly motivated by external or internal motivations. While the bulk of goal reasoning work has focused on agents that have implicit external motivations, internal motivations may offer some unique benefits to goal reasoning. As artificial internal motivations have a natural analogue to the human motivation system, this work investigates recent advances in motivated agents, where motivations are modeled on the human integrated-self. In this survey, we review those goal reasoning systems whose meta-reasoning and other goal reasoning subprocesses are at least in part intrinsic or identified, i.e., arising from idiosyncratic factors such as identity, a value system, emotions, experiences and so forth. For each system surveyed we evaluate its goal reasoning processes according to an analysis framework. We use our findings to draw conclusions about the potential benefits the three self-system categories: motives, mental simulation, and emotion bring to the goal reasoning paradigm.
期刊介绍:
Cognitive Systems Research is dedicated to the study of human-level cognition. As such, it welcomes papers which advance the understanding, design and applications of cognitive and intelligent systems, both natural and artificial.
The journal brings together a broad community studying cognition in its many facets in vivo and in silico, across the developmental spectrum, focusing on individual capacities or on entire architectures. It aims to foster debate and integrate ideas, concepts, constructs, theories, models and techniques from across different disciplines and different perspectives on human-level cognition. The scope of interest includes the study of cognitive capacities and architectures - both brain-inspired and non-brain-inspired - and the application of cognitive systems to real-world problems as far as it offers insights relevant for the understanding of cognition.
Cognitive Systems Research therefore welcomes mature and cutting-edge research approaching cognition from a systems-oriented perspective, both theoretical and empirically-informed, in the form of original manuscripts, short communications, opinion articles, systematic reviews, and topical survey articles from the fields of Cognitive Science (including Philosophy of Cognitive Science), Artificial Intelligence/Computer Science, Cognitive Robotics, Developmental Science, Psychology, and Neuroscience and Neuromorphic Engineering. Empirical studies will be considered if they are supplemented by theoretical analyses and contributions to theory development and/or computational modelling studies.