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Optimal Stopping with Behaviorally Biased Agents: The Role of Loss Aversion and Changing Reference Points
[article]
2021
arXiv
pre-print
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We formulate and study a behaviorally well-motivated version of the optimal stopping problem that incorporates these notions of reference dependence and loss aversion. ...
Here we explore the implications of reference points and loss aversion in optimal stopping problems, where people evaluate a sequence of options in one pass, either accepting the option and stopping the ...
We will refer to an agent with this behavior as a reference-dependent agent with loss-aversion λ. ...
arXiv:2106.00604v1
fatcat:ytjybwh3kbeulf7cktfxnoo5e4
Multi-Agent Inverse Reinforcement Learning: Suboptimal Demonstrations and Alternative Solution Concepts
[article]
2021
arXiv
pre-print
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We found that the primary methods for handling noise, biases and heuristics in MIRL were extensions of Maximum Entropy (MaxEnt) IRL to multi-agent settings. ...
Success in modeling specific biases and heuristics in single-agent IRL and promising results using a Theory of Mind approach in MIRL imply that modeling specific biases and heuristics may be useful. ...
This research was supported by the Stanford Existential Risk Initiative (SERI) and the Berkeley Existential Risk Initiative (BERI). ...
arXiv:2109.01178v1
fatcat:v635kuj4wfg4nndxvclbaubv2q
Deep CPT-RL: Imparting Human-Like Risk Sensitivity to Artificial Agents
2021
AAAI Conference on Artificial Intelligence
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The former ability may prevent catastrophic outcomes in unfamiliar settings while the latter results in asymmetric processing of potential gains and losses. ...
Reinforcement learning (RL) methods that consider edge behaviors are often referred to as risk-sensitive and have become increasingly well-studied as the prospects for realworld deployment of RL have grown ...
Acknowledgments The authors thank Ashley Llorens for insightful technical discussions and for his leadership of the Johns Hopkins Institute for Assured Autonomy (JHU IAA) project that supported our experimentation ...
dblp:conf/aaai/MarkowitzCW21
fatcat:ghqjrpdt2jabhmmqnal5eul5he
Bounded Rational Heterogeneous Agents In Artificial Stock Markets: Literature Review And Research Direction
2015
Zenodo
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We consider the roles of behavioral finance (BF) alongside the traditionally risk-averse assumption in the construction of agent's attributes. ...
Also, the influence of social networks in the developing of agents interactions is addressed. ...
ACKNOWLEDGMENT The authors would like to thank Dr.Ali Mostashari for his help and comments. ...
doi:10.5281/zenodo.1108121
fatcat:nvsrubo73nd4toeiw2ov7cokpa
Chapter 24 Agent-based Computational Finance
[chapter]
2006
Handbook of Computational Economics
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It will concentrate on models where the use of computational tools is critical for the process of crafting models which give insights into the importance and dynamics of investor heterogeneity in many ...
This chapter surveys research on agent-based models used in finance. ...
The latter brings in more realism at a cost of additional complexity in the learning process. It is also possible that certain behavioral features, such as loss aversion, should be included. ...
doi:10.1016/s1574-0021(05)02024-1
fatcat:alt63gfpovdzjihsydq3olgzei
Misperception of Risk and Incentives by Experienced Agents
2014
Social Science Research Network
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In the leading domain, they incorrectly exhibit decreasing absolute risk aversion with the magnitude of their lead. ...
When leading, risk aversion should increase with the lead, running counter to typical risk preferences. ...
The key test of optimality lies in the estimates of β 4 and β 5 . Proposition 4 states that optimal response to changing incentives over risk requires that both coefficients are negative. ...
doi:10.2139/ssrn.2435551
fatcat:bwh4x4cuojhmtkahchlxbcdi74
Role of information in decision making of social agents
[article]
2015
arXiv
pre-print
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The influence of additional information on the decision making of agents, who are interacting members of a society, is analyzed within the mathematical framework based on the use of quantum probabilities ...
The introduction of social interactions, which influence the decisions of individual agents, leads to a generalization of the quantum decision theory developed earlier by the authors for separate individuals ...
Acknowledgements The authors acknowledge financial support from the Swiss National Science Foundation. Useful discussions with E.P. Yukalova are appreciated. ...
arXiv:1510.02686v1
fatcat:p2lmehrq7jfszkljq4nl6jhwtu
Artificial Motivation for Cognitive Software Agents
2020
Journal of Artificial General Intelligence
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Natural selection has imbued biological agents with motivations moving them to act for survival and reproduction, as well as to learn so as to support both. ...
These include alarms, appraisal mechanisms, appetence and aversion, and deliberation and planning. ...
We present the details of this below and then discuss how such learning may lead to appetitive or aversive behavior. ...
doi:10.2478/jagi-2020-0002
fatcat:szpacc3cyzcwximrx7ubqcodo4
Goal bracketing and self-control
2018
Games and Economic Behavior
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In the presence of loss aversion and noisy observation of payoff processes, this decision involves a trade-off between motivation and comparative disutility due to ex-ante outcome uncertainty. ...
This paper studies the role of goal bracketing to attenuate time inconsistency. ...
Robustness Relative to Hsiaw (2013) , which used a single-stage stopping problem to analyze the behavior of present-biased agents with reference dependent preferences in the absence of loss aversion, ...
doi:10.1016/j.geb.2018.06.005
fatcat:hd6zkevlvzfzhluvtpble4gz4y
Goal Bracketing and Self-Control
2016
Social Science Research Network
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In the presence of loss aversion and noisy observation of payoff processes, this decision involves a trade-off between motivation and comparative disutility due to ex-ante outcome uncertainty. ...
This paper studies the role of goal bracketing to attenuate time inconsistency. ...
Robustness Relative to Hsiaw (2013) , which used a single-stage stopping problem to analyze the behavior of present-biased agents with reference dependent preferences in the absence of loss aversion, ...
doi:10.2139/ssrn.2864575
fatcat:wzb76o2bn5gutmpg744lmgymji
Analysis of Agent Expertise in Ms. Pac-Man using Value-of-Information-based Policies
2018
IEEE Transactions on Games
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This cost function is the value of information, which provides the optimal trade-off between the expected return of a policy and the policy's complexity; policy complexity is measured by number of bits ...
In this paper, we consider an information-theoretic cost function for performing constrained stochastic searches that promote the formation of risk-averse to risk-favoring behaviors. ...
We refer to this as the original score in our plots. For this score, the agent earns +10 and +50 points for consuming a pill and power pill, respectively. ...
doi:10.1109/tg.2018.2808201
fatcat:xfemrk6ru5dxnizxr56jl5jvdy
How to grow a bubble: A model of myopic adapting agents
[article]
2010
arXiv
pre-print
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We present a simple agent-based model to study the development of a bubble and the consequential crash and investigate how their proximate triggering factor might relate to their fundamental mechanism, ...
The model offers a simple reconciliation of the two opposite (herding versus fundamental) proposals for the origin of crashes within a single framework and justifies the existence of two populations in ...
Acknowledgments: We would like to thank Wei-Xing Zhou for invaluable discussions during the course of the project and Gilles Daniel and Ryan ...
arXiv:0806.2989v2
fatcat:76wnxb754fhnnchrfy24liok7a
Goal-setting and self-control
2013
Journal of Economic Theory
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Present-biased agents have linear reference-dependent preferences and endogenously set a goal that is the reference point. ...
In particular, reference dependence is strictly worse for a time-consistent agent. Notably, none of the effects of goal-setting require any form of loss aversion. ...
with gains and losses relative to a reference point, which here corresponds to his goal. ...
doi:10.1016/j.jet.2012.08.001
fatcat:qqfjcdqi7ndx7eh4mxfdv72d7i
Limited intelligence and performance-based compensation: An agent-based model of the hidden action problem
[article]
2021
arXiv
pre-print
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The principal's behavior appears to be driven by opportunism, as she withholds a premium from the agent to assure the optimal utility for herself. ...
We follow the agentization approach and introduce an agent-based version of the hidden action problem, in which some of the idealized assumptions about the principal and the agent are relaxed so that they ...
Most of these models assume intelligent agents who are rational in their behavior, employ optimization methods, usually possess all (or at least most) pieces of information to immediately come up with ...
arXiv:2107.03764v1
fatcat:afzrim4jynctzbplt7pvcxnwiu
Physics and financial economics (1776–2014): puzzles, Ising and agent-based models
2014
Reports on progress in physics (Print)
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The role of the Ising model of phase transitions to model social and financial systems is reviewed, with the concepts of random utilities and the logit model as the analog of the Boltzmann factor in statistic ...
The fundamentally different perspectives embraced in theories developed in financial economics compared with physics are dissected with the examples of the volatility smile and of the excess volatility ...
The atomistic, optimizing agents underlying existing models do not capture behavior during a crisis period. ...
doi:10.1088/0034-4885/77/6/062001
pmid:24875470
fatcat:mwqsvx5l35dsbck4ooxaqx2mzu
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