Abstract
There has been considerable work on reasoning about the strategic ability of agents under imperfect information. However, existing logics such as Probabilistic Strategy Logic are unable to express properties relating to information transparency. Information transparency concerns the extent to which agents’ actions and behaviours are observable by other agents. Reasoning about information transparency is useful in many domains including security, privacy, and decision-making. In this paper, we present a formal framework for reasoning about information transparency properties in stochastic multi-agent systems. We extend Probabilistic Strategy Logic with new observability operators that capture the degree of observability of temporal properties by agents. We show that the model checking problem for the resulting logic is decidable.
Original language | English |
---|---|
Title of host publication | Special Track on AI Alignment |
Editors | Toby Walsh, Julie Shah, Zico Kolter |
Publisher | Association for the Advancement of Artificial Intelligence |
Pages | 15092-15099 |
Number of pages | 8 |
Edition | 14 |
ISBN (Electronic) | 9781577358978 |
DOIs | |
Publication status | Published - 11 Apr 2025 |
Event | 39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025 - Philadelphia, United States Duration: 25 Feb 2025 → 4 Mar 2025 Conference number: 39 https://aaai.org/conference/aaai/aaai-25/ |
Publication series
Series | Proceedings of the AAAI Conference on Artificial Intelligence |
---|---|
Number | 14 |
Volume | 39 |
ISSN | 2159-5399 |
Conference
Conference | 39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025 |
---|---|
Abbreviated title | AAAI-25 |
Country/Territory | United States |
City | Philadelphia |
Period | 25/02/25 → 4/03/25 |
Internet address |