When communication between teammates is limited to observations of each other's actions, agents may need to improvise to stay coordinated. Unfortunately, current methods inadequately capture the uncertainty introduced by a lack of direct communication. This paper augments existing frameworks to introduce Simple Temporal Networks for Improvisational Teamwork (STN-IT)—a formulation that captures both the temporal dependencies and uncertainties between agents who need to coordinate but lack reliable communication. We define the notion of strong controllability for STN-ITs, which establishes a static scheduling strategy for controllable agents that produces a consistent team schedule, as long as non-communicative teammates act within known problem constraints. We provide both an exact and approximate approach for finding strongly controllable schedules, empirically demonstrate the trade-offs between these approaches on benchmarks of STN-ITs, and show analytically that the exact method is correct.
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Simple Temporal Networks for Improvisational Teamwork
When communication between teammates is limited to observations of each other’s actions, agents may need to improvise to stay coordinated. Unfortunately, current methods inadequately capture the uncertainty introduced by a lack of direct communication. This paper augments existing frameworks to introduce Simple Temporal Networks for Improvisational Teamwork (STN-IT) — a formulation that captures both the temporal dependencies and uncertainties between agents who need to coordinate, but lack reliable communication. We define the notion of strong controllability for STN-ITs, which establishes a static scheduling strategy for controllable agents that produces a consistent team schedule, as long as non-communicative teammates act within known problem constraints. We provide both an exact and approximate approach for finding strongly controllable schedules, empirically demonstrate the trade-offs between these two approaches on a benchmark of STN-ITs, and show analytically that the exact method is correct. In addition, we provide an empirical analysis of the exact and approximate approaches’ efficiency
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- Award ID(s):
- 1651822
- NSF-PAR ID:
- 10321758
- Date Published:
- Journal Name:
- AAAI Spring Symposium Series on Can We Talk? How to Design Multi-Agent Systems In the Absence of Reliable Communications
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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