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A Survey and Critique of Multiagent Deep Reinforcement Learning
[article]
<span title="2019-06-22">2019</span>
<i >
arXiv
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<span class="release-stage" >pre-print</span>
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<span title="2018-10-12">2018</span>
<span class="release-stage" >pre-print</span>
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<span title="2019-08-30">2019</span>
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The primary goal of this article is to provide a clear overview of current multiagent deep reinforcement learning (MDRL) literature. ...
Deep reinforcement learning (RL) has achieved outstanding results in recent years. This has led to a dramatic increase in the number of applications and methods. ...
and three anonymous reviewers whose comments and suggestions increased the quality of this work. 56 The title of this work makes a clear reference to previous seminal MAL works [2, 354] . ...
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Multi-UAV Conflict Resolution with Graph Convolutional Reinforcement Learning
<span title="2022-01-09">2022</span>
<i title="MDPI AG">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/smrngspzhzce7dy6ofycrfxbim" style="color: black;">Applied Sciences</a>
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In this paper, we model multi-UAV conflict resolution as a multiagent reinforcement learning problem. ...
The model is evaluated in scenarios with 3 and 4 present agents. Results show that agents are able to successfully solve the multi-UAV conflicts through a cooperative strategy. ...
A survey and critique of multiagent deep reinforcement learning. Auton. Agents
Multi-Agent Syst. 2019, 33, 750–797. [CrossRef]
34. Bellman, R. ...
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A Survey on Transfer Learning for Multiagent Reinforcement Learning Systems
<span title="2019-03-11">2019</span>
<i title="AI Access Foundation">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/4ax4efcwajcgvidb6hcg6mwx4a" style="color: black;">The Journal of Artificial Intelligence Research</a>
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This survey provides a unifying view of the literature on knowledge reuse in multiagent RL. ...
Multiagent Reinforcement Learning (RL) solves complex tasks that require coordination with other agents through autonomous exploration of the environment. ...
Taylor for the collaboration in previous versions of this survey. ...
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Decentralized Multiagent Actor-Critic Algorithm Based on Message Diffusion
<span title="2021-12-08">2021</span>
<i title="Hindawi Limited">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/zlknqk4ahbcsthbafxw55emm7a" style="color: black;">Journal of Sensors</a>
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To overcome these problems, in this paper, we propose a model-free and fully decentralized actor-critic multiagent reinforcement learning algorithm based on message diffusion. ...
The exponential explosion of joint actions and massive data collection are two main challenges in multiagent reinforcement learning algorithms with centralized training. ...
Taylor, “A very con-
densed survey and critique of multiagent deep reinforcement ...
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Advancing Automation in Digital Forensic Investigations Using Machine Learning Forensics
[chapter]
<span title="2019-12-17">2019</span>
<i title="IntechOpen">
Digital Forensic Science [Working Title]
</i>
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As a result of this transformation, we are becoming the soft target of various types of cybercrimes. ...
Laptops, tablets, smartphones and wearable devices are the major source of this digital data transformation and are becoming the core part of our daily life. ...
We present the latest surveys in this field and give critique comparisons of these approaches. ...
<span class="external-identifiers">
<a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5772/intechopen.90233">doi:10.5772/intechopen.90233</a>
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2020 Index IEEE Transactions on Systems, Man, and Cybernetics: Systems Vol. 50
<span title="">2020</span>
<i title="Institute of Electrical and Electronics Engineers (IEEE)">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/whrz22ivnbhwbbeoexygwc4ybq" style="color: black;">IEEE Transactions on Systems, Man & Cybernetics. Systems</a>
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The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination. ...
The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author's name, the publication abbreviation, month, and year, and inclusive pages. ...
., +, TSMC June 2020 2220-2230 cations: A Survey of Trends and Techniques. ...
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Deep Reinforcement Learning Versus Evolution Strategies: A Comparative Survey
[article]
<span title="2021-09-28">2021</span>
<i >
arXiv
</i>
<span class="release-stage" >pre-print</span>
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Deep Reinforcement Learning (DRL) and Evolution Strategies (ESs) have surpassed human-level control in many sequential decision-making problems, yet many open challenges still exist. ...
Finally, to have an indication about how they compare in real-world applications, a survey of the literature for the set of applications they support is provided. ...
Fig. 1 : 1 The structure of the survey robot (agent)
Fig. 2 : 2 Iteration loops of (Deep) Reinforcement Learning and Evolutionary Strategies. ...
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Towards Resilient Artificial Intelligence: Survey and Research Issues
[article]
<span title="2021-09-18">2021</span>
<i >
arXiv
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<span class="release-stage" >pre-print</span>
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<span title="2021-07-26">2021</span>
<i >
2021 IEEE International Conference on Cyber Security and Resilience (CSR)
</i>
<span class="release-stage">unpublished</span>
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/csr51186.2021.9527986">doi:10.1109/csr51186.2021.9527986</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/lgty4bnk6nf6fp54vhz3fhakme">fatcat:lgty4bnk6nf6fp54vhz3fhakme</a> </span>
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Considering the particular nature of AI, and machine learning (ML) in particular, this paper provides an overview of the emerging field of resilient AI and presents research issues the authors identify ...
Their resilience against attacks and other environmental influences needs to be ensured just like for other IT assets. ...
Figure 1 : 1 Survey dimensions and identified research issues
Resilience Testing and Monitoring Deep Learning
Reinforcement
Learning
Model Evaluation
and Operations
Data Preparation
and Management ...
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Reports of the AAAI 2014 Conference Workshops
<span title="2015-03-25">2015</span>
<i title="Association for the Advancement of Artificial Intelligence (AAAI)">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/27wksbinzzhjfow2wuy6m2iefm" style="color: black;">The AI Magazine</a>
</i>
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The AAAI-14 workshop program included fifteen workshops covering a wide range of topics in artificial intelligence. ...
and Imperfect Information; Discovery Informatics; Incentives and Trust in Electronic Communities; Intelligent Cinematography and Editing; Machine Learning for Interactive Systems: Bridging the Gap between ...
Buckeridge, and John S. Brownstein served as cochairs of this workshop. The papers of the symposium were published as AAAI Press Technical Report WS-14-14. ...
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A Conceptual Framework for Externally-influenced Agents: An Assisted Reinforcement Learning Review
[article]
<span title="2020-07-03">2020</span>
<i >
arXiv
</i>
<span class="release-stage" >pre-print</span>
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<span title="2021-09-20">2021</span>
<span class="release-stage">accepted</span>
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A long-term goal of reinforcement learning agents is to be able to perform tasks in complex real-world scenarios. ...
In this work, we propose a conceptual framework and taxonomy for assisted reinforcement learning, aimed at fostering such collaboration by classifying and comparing various methods that use external information ...
Acknowledgments This work has been partially supported by the Australian Government Research Training Program (RTP) and the RTP Fee-Offset Scholarship through Federation University Australia. ...
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Deep Reinforcement Learning
[article]
<span title="2018-10-15">2018</span>
<i >
arXiv
</i>
<span class="release-stage" >pre-print</span>
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We start with background of artificial intelligence, machine learning, deep learning, and reinforcement learning (RL), with resources. ...
We discuss deep reinforcement learning in an overview style. We draw a big picture, filled with details. ...
The authors propose policy-space response oracle (PSRO), and its approximation, deep cognitive hierarchies (DCH), to compute best responses to a mixture of policies using deep RL, and to compute new meta-strategy ...
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Reinforcement learning based recommender systems: A survey
[article]
<span title="2021-01-15">2021</span>
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arXiv
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In this paper, a survey on reinforcement learning based recommender systems (RLRSs) is presented. ...
Accordingly, it can be formulated as a Markov decision process (MDP) and reinforcement learning (RL) methods can be employed to solve it. ...
learning, and deep reinforcement learning. ...
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Human-in-the-Loop Methods for Data-Driven and Reinforcement Learning Systems
[article]
<span title="2020-08-30">2020</span>
<i >
arXiv
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Recent successes combine reinforcement learning algorithms and deep neural networks, despite reinforcement learning not being widely applied to robotics and real world scenarios. ...
Results presented in this work show that the reward signal that is learned based upon human interaction accelerates the rate of learning of reinforcement learning algorithms and that learning from a combination ...
Agents and MultiAgent Systems. ...
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AAAI News
<span title="">2003</span>
<i title="Association for the Advancement of Artificial Intelligence (AAAI)">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/27wksbinzzhjfow2wuy6m2iefm" style="color: black;">The AI Magazine</a>
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of planning and learning algo-
learning and stochastic planning, to dia- rithms, and multiagent robot teams for
logue agents, and to the theory ...
Bob had deep interests in both the technical and
entrepreneurial aspects of AI. ...
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<a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1609/aimag.v24i2.1711">doi:10.1609/aimag.v24i2.1711</a>
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The Association for the Advancement of Artificial Intelligence 2020 Workshop Program
<span title="2020-12-28">2020</span>
<i title="Association for the Advancement of Artificial Intelligence (AAAI)">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/27wksbinzzhjfow2wuy6m2iefm" style="color: black;">The AI Magazine</a>
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The Association for the Advancement of Artificial Intelligence 2020 Workshop Program included twenty-three workshops covering a wide range of topics in artificial intelligence. ...
This report contains the required reports, which were submitted by most, but not all, of the workshop chairs. ...
The concrete techniques ranged from symbolic logical reasoning to neural network-based deep learning and reinforcement learning. ...
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