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Emergent Bartering Behaviour in Multi-Agent Reinforcement Learning [article]

Michael Bradley Johanson, Edward Hughes, Finbarr Timbers, Joel Z. Leibo
2022 arXiv   pre-print
in prior multi-agent reinforcement learning work along several dimensions.  ...  Agents learn to produce resources in a spatially complex world, trade them with one another, and consume those that they prefer.  ...  Multi-agent reinforcement learning In multi-agent reinforcement learning, a population of reinforcement learning agents learn through interactions with each other in a shared environment.  ... 
arXiv:2205.06760v1 fatcat:p4ebfpkornderpnnq6ftf7ulde

From Conditional Commitments to Generalized Media: On Means of Coordination Between Self-Governed Entities [chapter]

Ingo Schulz-Schaeffer
2005 Lecture Notes in Computer Science  
The conceptual framework resulting from the considerations is applicable to coordination problems between human actors as well as to coordination problems between artificial agents in open multi-agent  ...  In this paper, the motivating conditional self-commitment is conceived to be the basic mechanism to solve coordination problems of this kind.  ...  In the first setting the agents learn about other agents' behaviour only from their own experiences, in the second setting they exchange their experiences.  ... 
doi:10.1007/11594116_12 fatcat:d2bqll5z4ffijcnnu6zpsvc6au

Simulating Social and Economic Specialization in Small-Scale Agricultural Societies

Denton Cockburn, Stefani A. Crabtree, Ziad Kobti, Timothy A. Kohler, R. Kyle Bocinsky
2013 Journal of Artificial Societies and Social Simulation  
The networks generated by barter in the latter scenario exhibit higher clustering coefficients, suggesting that social influence allows a few agents to assume particularly influential roles in the global  ...  Agents exchange and request goods using barter, balanced reciprocal exchange, and generalized reciprocal exchange.  ...  if successful, selecting that action in the next round with higher probability. 1.8 For reinforcement-based systems to succeed in dynamic environments, agents must be able to overcome previously learned  ... 
doi:10.18564/jasss.2308 fatcat:vyztadzngnfl3ddlq6shxqdfoq

Agent-based models of financial markets

E Samanidou, E Zschischang, D Stauffer, T Lux
2007 Reports on progress in physics (Print)  
Our selective review then outlines the main ingredients of some influential early models of multi-agent dynamics in financial markets (Kim-Markowitz, Levy-Levy-Solomon).  ...  From the wealth of different flavours of multi-agent models that have appeared up to now, we discuss the Cont-Bouchaud, Solomon-Levy-Huang and Lux-Marchesi models.  ...  stuck in a situation of barter trade.  ... 
doi:10.1088/0034-4885/70/3/r03 fatcat:pdjyg6irnfa75civru3illktli

Simulating information sharing in crisis response coalitions as a minority game

Ariën J. van der Wal, Tim J. Grant
2013 International Conference on Information Systems for Crisis Response and Management  
Differences in organizational culture give information a scarcity value, leading to the emergence of information markets.  ...  As the crisis progresses, organizations learn to work together, building up trust and lowering the "price" for information shared.  ...  Adaptation in the MG is equivalent to reinforcement learning. However, the simplicity of the MG is also its source of limitations.  ... 
dblp:conf/iscram/WalG13 fatcat:fx6qwrxganfjdditg5eotshkwy

Intelligent Software Web Agents: A Gap Analysis [article]

Sabrina Kirrane
2021 arXiv   pre-print
In order to better understand the existing technological opportunities and challenges, in this paper we examine the status quo in terms of intelligent software web agents, guided by research with respect  ...  for emerging domains, such as digital assistants, cloud computing, and the internet of things.  ...  Broadly speaking, existing proposals focus on using ontology or reinforcement learning techniques to enhance the agents knowledge base, or demonstrating how agents can adapt their behaviour based on changes  ... 
arXiv:2102.06607v3 fatcat:5hqx4c6vevbonmyjetipw4ljyu

Reward Bases: Instantaneous reward revaluation with temporal difference learning [article]

Beren Millidge, Mark Walton, Rafal Bogacz
2022 bioRxiv   pre-print
An influential theory posits that dopaminergic neurons in the mid-brain implement a model-free reinforcement learning algorithm based on temporal difference (TD) learning.  ...  We demonstrate that our algorithm can also reproduce behavioural data on reward revaluation tasks, predict dopamine responses in the nucleus accumbens, as well as learn equally fast as successor representations  ...  Acknowledgements The authors would like to thank Nathaniel Daw and Scott Waddell for discussion and Mycah Banks for her aid in preparing the figures.  ... 
doi:10.1101/2022.04.14.488361 fatcat:dazgkqs4hfblxmcd5u6l4xkcoi

Modeling Organizations and Institutions in Multiagent Systems

Nicoletta Fornara, Tina Balke-Visser
2018 IfColog journal of logics and their applications (FLAP)  
The NorMAS initiative aims at providing a comprehensive coverage of both the state of the art and future research perspectives in the interdisciplinary field of normative multi-agent systems.  ...  This special issue contains the journal version of four contributions to the Handbook of Normative Multi-Agent Systems (NorMAS), which will appear at College Publications.  ...  using machine learning (commonly reinforcement learning in the form of Q-learning [Watkins and Dayan, 1992] ).  ... 
dblp:journals/flap/FornaraB18 fatcat:sm57tnnapbbwha2y43asag5pxy

Money as tool, money as drug: The biological psychology of a strong incentive

Stephen E. G. Lea, Paul Webley
2006 Behavioral and Brain Sciences  
Why are people interested in money? Specifically, what could be the biological basis for the extraordinary incentive and reinforcing power of money, which seems to be unique to the human species?  ...  We identify two ways in which a commodity which is of no biological significance in itself can become a strong motivator.  ...  So, once the use of money is learned by agents in a barter environment, a dopamine-based system takes over.  ... 
doi:10.1017/s0140525x06009046 pmid:16606498 fatcat:w5fvcxlp65gxpjnbixtssmg44u

Artificial intelligence based cognitive routing for cognitive radio networks

Junaid Qadir
2015 Artificial Intelligence Review  
We discuss various decision making techniques and learning techniques from AI and document their current and potential applications to the problem of routing in CRNs.  ...  In this paper, we provide a self-contained tutorial on various AI and machine-learning techniques that have been, or can be, used for developing cognitive routing protocols.  ...  properly envisioned in multi-agent learning which are more challenging that single-agent learning scenario.  ... 
doi:10.1007/s10462-015-9438-6 fatcat:hi4mk5iaf5dsjgco5sgknejroq

Learning subversion in the business school: An 'improbable' encounter

Sylvain P Bureau, Aris Komporozos-Athanasiou
2016 Management Learning  
Drawing on the theory of Bakhtin, which has thus far been overlooked in entrepreneurship studies, we unpick the potentiality of art practices in the learning and experiencing of the subversive dimension  ...  We show how 'subversive dialogues' are enacted between students and teachers as they engage in the learning process and discuss implications for critical entrepreneurship teaching in an increasingly commoditized  ...  'traditional patterns of behaviour' (Smilor, 1997) .  ... 
doi:10.1177/1350507616661262 fatcat:sel6q7vqfvez3k5a35pxp2y7w4

The firm/territory relationships in the globalisation: towards a new rationale

Jean-Benoit Zimmermann
2001 European Journal of Economic and Social Systems  
In terms of formal models, research works are at the very first step. Nevertheless, an approach in terms of "small worlds" seems to present very fruitful perspectives.  ...  A concrete illustration is extensively developed about SGS-Thomson Microelectronics group with regard to its productive site in Rousset, in the French Bouches-du-Rhône district.  ...  In an other paper (Plouraboué et al., 1998) we have introduced a social learning process, in which agents that share the same opinion tend to reinforce their links.  ... 
doi:10.1051/ejess:2001108 fatcat:g3r2hvznrrfyzovgaxdo7vrhau

An Economics of Wellbeing: What Would Economics Look Like if it were Focused on Human Wellbeing?

Nicky Pouw, Allister McGregor
2014 IDS Working Papers  
In particular, the paper draws on heterodox economics to redefine the scope of economics, economic agency, rational behaviour and put emphasis on wellbeing rather than welfare.  ...  It emerges from a pluralist perspective in economics and the ontological, conceptual, axiomatic and methodological propositions that are made lead to the construction of what we call an inclusive economy  ...  Acknowledgements An earlier version of this paper was presented at the Oxford/OU Conference 'Economics for a Better World' that took place at the Organisation for Economic Co-operation and Development (OECD) in  ... 
doi:10.1111/j.2040-0209.2014.00436.x fatcat:blkgs3gprfhmjaadsomn7oesaq

Information sharing through informal interaction in low-tech clusters

Anant Kamath
2015 Innovation and Development  
ISBN 978 94 6159 279 8 © Anant Kamath, Maastricht 2013 Cover Image Cotton stacks and 'churka' or cotton gin in operation, Berar, India (1866) v Acknowledgements In Indian mythology there is a story of  ...  The various 'eyes' in this thesis were aimed at with this sort of holistic and broad perspective of each issue, however small, keeping in mind the broader socio-economic and institutional environment around  ...  If the imitated behaviour is rewarded well, it is reinforced and stabilises.  ... 
doi:10.1080/2157930x.2015.1007570 fatcat:sknsjoxsajcqlpilldd3skjzn4

All One Needs to Know about Metaverse: A Complete Survey on Technological Singularity, Virtual Ecosystem, and Research Agenda [article]

Lik-Hang Lee, Tristan Braud, Pengyuan Zhou, Lin Wang, Dianlei Xu, Zijun Lin, Abhishek Kumar, Carlos Bermejo, Pan Hui
2021 arXiv   pre-print
Since the popularisation of the Internet in the 1990s, the cyberspace has kept evolving.  ...  While the metaverse may seem futuristic, catalysed by emerging technologies such as Extended Reality, 5G, and Artificial Intelligence, the digital 'big bang' of our cyberspace is not far away.  ...  There are three categories in machine learning: supervised learning, unsupervised learning, and reinforcement learning.  ... 
arXiv:2110.05352v3 fatcat:pv4fxf5lfbc7vk3ogsyidwfloy
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