The Artificial Agent

2021 ◽  
pp. 7-22
Keyword(s):  
Artificial Agent

Automated argument adjudication to solve ethical problems in multi-agent environments

2021 ◽  
Vol 12 (1) ◽  
pp. 310-335
Author(s):  
Selmer Bringsjord ◽  
Naveen Sundar Govindarajulu ◽  
Michael Giancola
Keyword(s):  
Ethical Problem ◽  
Propositional Content ◽  
Ethical Principles ◽  
Artificial Agents ◽  
Artificial Agent ◽  
Ethical Problems ◽  
Multi Agent

Abstract Suppose an artificial agent a adj {a}_{\text{adj}} , as time unfolds, (i) receives from multiple artificial agents (which may, in turn, themselves have received from yet other such agents…) propositional content, and (ii) must solve an ethical problem on the basis of what it has received. How should a adj {a}_{\text{adj}} adjudicate what it has received in order to produce such a solution? We consider an environment infused with logicist artificial agents a 1 , a 2 , … , a n {a}_{1},{a}_{2},\ldots ,{a}_{n} that sense and report their findings to “adjudicator” agents who must solve ethical problems. (Many if not most of these agents may be robots.) In such an environment, inconsistency is a virtual guarantee: a adj {a}_{\text{adj}} may, for instance, receive a report from a 1 {a}_{1} that proposition ϕ \phi holds, then from a 2 {a}_{2} that ¬ ϕ \neg \phi holds, and then from a 3 {a}_{3} that neither ϕ \phi nor ¬ ϕ \neg \phi should be believed, but rather ψ \psi instead, at some level of likelihood. We further assume that agents receiving such incompatible reports will nonetheless sometimes simply need, before long, to make decisions on the basis of these reports, in order to try to solve ethical problems. We provide a solution to such a quandary: AI capable of adjudicating competing reports from subsidiary agents through time, and delivering to humans a rational, ethically correct (relative to underlying ethical principles) recommendation based upon such adjudication. To illuminate our solution, we anchor it to a particular scenario.

What is it like to encounter an autonomous artificial agent?

AI & Society ◽  
2013 ◽  
Vol 28 (4) ◽  
pp. 483-489 ◽  
Author(s):  
Karsten Weber
Keyword(s):  
Artificial Agent

scholarly journals Development of Intelligent Multi-agents System for Collaborative e-learning Support

2018 ◽  
Vol 7 (2) ◽  
pp. 294-305
Author(s):  
Issam Matazi ◽  
Rochdi Messoussi ◽  
Salah-Eddine Bellmallem ◽  
Ilham Oumaira ◽  
Abdellah Bennane ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Learning Support ◽  
Artificial Agent ◽  
Learning Collaborative ◽  
Collaborative System ◽  
Pedagogical Action ◽  
E Learning ◽  
Multi Agents

The aim of this paper is the introduction of intelligence in e-learning collaborative system. In such system, the tutor plays an important role to facilitate collaboration between users and boost less active among them to get more involved for good pedagogical action. However, the problem lies in the large number of platform users, and the tutor tasks become difficult if not impossible. Therefore, we used fuzzy logic technics in order to solve this problem by automating tutor tasks and creating an artificial agent. This agent is elaborate in basing on the learners activities, especially the assessment of their collaborative behaviors. After the implementation of intelligent collaborative system by using Moodle platform, we have tested it. The reader will discover our approach and relevant results.

scholarly journals On the Adaptability of Recurrent Neural Networks for Real-Time Jazz Improvisation Accompaniment

2021 ◽  
Vol 3 ◽  
Author(s):  
Kosmas Kritsis ◽  
Theatina Kylafi ◽  
Maximos Kaliakatsos-Papakostas ◽  
Aggelos Pikrakis ◽  
Vassilis Katsouros
Keyword(s):  
Neural Networks ◽  
Real Time ◽  
Recurrent Neural Networks ◽  
Test Case ◽  
Jazz Improvisation ◽  
Artificial Agent ◽  
Separate Model ◽  
Subjective Evaluations ◽  
Refinement Process ◽  
Lead Sheet

Jazz improvisation on a given lead sheet with chords is an interesting scenario for studying the behaviour of artificial agents when they collaborate with humans. Specifically in jazz improvisation, the role of the accompanist is crucial for reflecting the harmonic and metric characteristics of a jazz standard, while identifying in real-time the intentions of the soloist and adapt the accompanying performance parameters accordingly. This paper presents a study on a basic implementation of an artificial jazz accompanist, which provides accompanying chord voicings to a human soloist that is conditioned by the soloing input and the harmonic and metric information provided in a lead sheet chart. The model of the artificial agent includes a separate model for predicting the intentions of the human soloist, towards providing proper accompaniment to the human performer in real-time. Simple implementations of Recurrent Neural Networks are employed both for modeling the predictions of the artificial agent and for modeling the expectations of human intention. A publicly available dataset is modified with a probabilistic refinement process for including all the necessary information for the task at hand and test-case compositions on two jazz standards show the ability of the system to comply with the harmonic constraints within the chart. Furthermore, the system is indicated to be able to provide varying output with different soloing conditions, while there is no significant sacrifice of “musicality” in generated music, as shown in subjective evaluations. Some important limitations that need to be addressed for obtaining more informative results on the potential of the examined approach are also discussed.

Norm Emergence in Multi-Agent Societies

2011 ◽  
pp. 195-206
Author(s):  
Bastin Tony Roy Savarimuthu ◽  
Maryam Purvis ◽  
Stephen Cranefield
Keyword(s):  
Software Agents ◽  
Experimental Results ◽  
Multi Agent System ◽  
Artificial Agent ◽  
Agent System ◽  
Agent Societies ◽  
Multi Agent ◽  
Norm Emergence

Norms are shared expectations of behaviours that exist in human societies. Norms help societies by increasing the predictability of individual behaviours and by improving cooperation and collaboration among members. Norms have been of interest to multi-agent system researchers, as software agents intend to follow certain norms. But, owing to their autonomy, agents sometimes violate norms, which needs monitoring. In order to build robust MAS that are norm compliant and systems that evolve and adapt norms dynamically, the study of norms is crucial. Our objective in this chapter is to propose a mechanism for norm emergence in artificial agent societies and provide experimental results. We also study the role of autonomy and visibility threshold of an agent in the context of norm emergence.

A multidisciplinary perspective on multi-agent systems

2000 ◽  
Vol 15 (3) ◽  
pp. 293-301
Author(s):  
EDMUND CHATTOE ◽  
KERSTIN DAUTENHAHN ◽  
IAN DICKINSON ◽  
JIM DORAN ◽  
NIR VULKAN
Keyword(s):  
Artificial Agent ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Engineering Discipline ◽  
Key Points ◽  
Computer Scientists ◽  
Multi Agent ◽  
Multidisciplinary Perspective ◽  
Computational Systems

The theory, principles and practice of multi-agent systems is typically characterised as a computational and engineering discipline, since it is through the medium of computational systems that artificial agent systems are most commonly expressed. However, most definitions of agency draw directly on non-computational disciplines for inspiration. During the 1999 UK workshop on multi-agent systems, UKMAS'99, we invited four speakers to address the conceptualisation of multi-agent systems from their perspective as non-computer scientists. This paper presents their arguments and summarises some of the key points of discussion during the panel.

Is the Extension of Trading Hours Always Beneficial? An Artificial Agent-Based Analysis

2016 ◽  
Vol 50 (4) ◽  
pp. 595-627 ◽  
Author(s):  
Kotaro Miwa ◽  
Kazuhiro Ueda
Keyword(s):  
Artificial Agent ◽  
Agent Based

Integration of an Autonomous Artificial Agent in an Insect Society: Experimental Validation

2006 ◽  
pp. 703-712 ◽  
Author(s):  
Grégory Sempo ◽  
Stéphanie Depickère ◽  
Jean-Marc Amé ◽  
Claire Detrain ◽  
José Halloy ◽  
...  
Keyword(s):  
Experimental Validation ◽  
Artificial Agent

The Theory of Cognitive Consciousness, and Λ (Lambda)

2020 ◽  
Vol 07 (02) ◽  
pp. 155-181
Author(s):  
Selmer Bringsjord ◽  
G. Naveen Sundar
Keyword(s):  
Formal Theory ◽  
Artificial Agent ◽  
Doctrine Of Double Effect ◽  
Axiomatic Theory ◽  
Ethical Decisions ◽  
Auguste Dupin ◽  
Different Dimensions ◽  
Edgar Allen Poe ◽  
Integrated Information Theory ◽  
Theory Formula

We provide an overview of the theory of cognitive consciousness (TCC), and of [Formula: see text]; the latter provides a means of measuring the amount of cognitive consciousness present in a given cognizer, whether natural or artificial, at a given time, along a number of different dimensions. TCC and [Formula: see text] stand in stark contrast to Tononi’s Integrated information Theory (IIT) and [Formula: see text]. We believe, for reasons we present, that the former pair is superior to the latter. TCC includes a formal axiomatic theory, [Formula: see text], the 12 axioms of which we present and briefly comment upon herein; no such formal theory accompanies IIT/[Formula: see text]. TCC/[Formula: see text] and IIT/[Formula: see text] each offer radically different verdicts as to whether and to what degree AIs of yesterday, today, and tomorrow were/are/will be conscious. Another noteworthy difference between TCC/[Formula: see text] and IIT/[Formula: see text] is that the former enables the measurement of cognitive consciousness in those who have passed on, and in fictional characters; no such enablement is remotely possible for IIT/[Formula: see text]. For instance, we apply [Formula: see text] to measure the cognitive consciousness of: Descartes; and the first fictional detective to be described on Earth (by Edgar Allen Poe), Auguste Dupin. We also apply [Formula: see text] to compute the cognitive consciousness of an artificial agent able to make ethical decisions using the Doctrine of Double Effect.

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