Michael W. Floyd

444 citations
20 papers · 126 · h-index 7

Impact in

    • AI-based Problem Solving and Planning
    • Reinforcement Learning in Robotics
    • Artificial Intelligence in Games
    • Multi-Agent Systems and Negotiation
    • Machine Learning and Algorithms

Papers in

Michael W. Floyd

18 papers receiving 115 citations

Peers

Michael W. Floyd
Comparison fields: 5 of 41
  • Artificial Intelligence 95
  • Software 4
  • Computer Vision and Pattern Recognition 19
  • Control and Systems Engineering 20
  • Social Psychology 14
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Citations per year

Countries citing papers authored by Michael W. Floyd

Since Specialization
Citations

This map shows the geographic impact of Michael W. Floyd's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Michael W. Floyd with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael W. Floyd more than expected).

Fields of papers citing papers by Michael W. Floyd

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael W. Floyd. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Michael W. Floyd. The network helps show where Michael W. Floyd may publish in the future.

Co-authors

The 11 scholars most cited alongside Michael W. Floyd, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Michael W. Floyd Line = papers co-authored together Michael W. Floyd links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1
A Case-based Reasoning Approach to Imitating RoboCup Players
200846
2 201118
3 20178
4 20177
5
Spy the Lie: Former CIA Officers Teach You How to Detect Deception
20127
6
Case-Based Learning by Observation in Robotics Using a Dynamic Case Representation
20126
7
Goal Reasoning for an Autonomous Squad Member
20156
8
Trust-guided behavior adaptation using case-based reasoning
20154
9 20184
10
Towards Deception Detection in a Language-Driven Game.
20173
11
Supplemental Case Acquisition Using Mixed-Initiative Control
20113
12 20183
13
Using Deep Learning to Automate Feature Modeling in Learning by Observation: A Preliminary Study.
20172
14
Case-Based Behavior Adaptation Using an Inverse Trust Metric
20142
15
Dynamic Goal Recognition Using Windowed Action Sequences.
20172
16
A Comparison of Case Acquisition Strategies for Learning from Observations of State-Based Experts.
20131
17 20101
18
Using Deep Learning to Automate Feature Modeling in Learning by Observation.
20171
19
Error Tolerant Plan Recognition: An Empirical Investigation
20151
20 20201

About Michael W. Floyd

Michael W. Floyd is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Control and Systems Engineering, Software and Social Psychology, having authored 20 papers that have together received 126 indexed citations. Recurring topics across this work include AI-based Problem Solving and Planning (14 papers), Multi-Agent Systems and Negotiation (7 papers), Artificial Intelligence in Games (3 papers), Logic, Reasoning, and Knowledge (3 papers), Robot Manipulation and Learning (2 papers), Guidance and Control Systems (2 papers), Machine Learning and Data Classification (2 papers) and Machine Learning and Algorithms (2 papers). The work is most often cited by research in Artificial Intelligence (95 citations), Software (4 citations), Computer Vision and Pattern Recognition (19 citations), Control and Systems Engineering (20 citations) and Social Psychology (14 citations). Michael W. Floyd has collaborated with scholars based in United States and Canada. Frequent co-authors include Babak Esfandiari, David W. Aha, Philip Moore, D. M. Tennant, M. J. Drinkwater, Matthew Molineaux, Gabriel Wainer, Santiago Ontañón, Swaroop Vattam and Dongkyu Choi. Their work appears in journals such as Applied Intelligence, AI Communications, The Florida AI Research Society, International Conference on Artificial Intelligence and National Conference on Artificial Intelligence.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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