Daigo Shishika
Papers
15
Total Citations
185
H-Index
7
About
Daigo Shishika is a robotics and autonomous systems researcher whose work sits at the intersection of multi-robot coordination, game theory, and adversarial decision-making. He has established a strong reputation for advancing the theory and practice of pursuit-evasion and perimeter defense problems, developing rigorous frameworks that determine how teams of robots should be composed, deployed, and coordinated to intercept intruders or protect sensitive regions under realistic constraints such as limited sensing and partial information. His 2019 paper on team composition for perimeter defense (39 citations) and his 2020 work on adaptive partitioning (30 citations) are particularly influential, providing foundational insights into how defender teams can be optimally structured against adversarial agents. Shishika further extended these ideas into target defense games with incomplete information (27 citations) and dynamic Defender-Attacker Blotto games on graphs (22 citations), demonstrating breadth across both continuous and discrete adversarial settings. His contributions to resilient consensus in robot swarms (24 citations) address the critical challenge of maintaining coordination despite adversarial or non-cooperative agents. Collectively accumulating over 170 citations, his body of work offers both theoretical depth and practical relevance for students and researchers designing robust, intelligent multi-robot systems.
Research Focus
Key Achievements
Top Papers
- 1Team Composition for Perimeter Defense with Patrollers and Defenders39 citations · 2019
- 2Adaptive Partitioning for Coordinated Multi-agent Perimeter Defense30 citations · 2020
- 3Partial Information Target Defense Game27 citations · 2021
- 4
- 5Dynamic Defender-Attacker Blotto Game22 citations · 2022
- 6Modular Robot Formation and Routing for Resilient Consensus10 citations · 2020
- 7Optimal Multi-robot Perimeter Defense Using Flow Networks8 citations · 2022
- 8
- 9Decentralization of Multiagent Policies by Learning What to Communicate4 citations · 2019
- 10