Approximating perfect recall when model checking strategic abilities
File(s)kr18-BLM.pdf (297.19 KB)
Accepted version
Author(s)
Lomuscio, AR
Belardinelli, F
malvone, V
Type
Conference Paper
Abstract
We investigate the notion of bounded recall in the context
of model checking
ATL
∗
and
ATL
specifications in multi-
agent systems with imperfect information. We present a novel
three-valued semantics for
ATL
∗
, respectively
ATL
, under
bounded recall and imperfect information, and study the cor-
responding model checking problems. Most importantly, we
show that the three-valued semantics constitutes an approxi-
mation with respect to the traditional two-valued semantics.
In the light of this we construct a sound, albeit partial, al-
gorithm for model checking two-valued perfect recall via its
approximation as three-valued bounded recall.
of model checking
ATL
∗
and
ATL
specifications in multi-
agent systems with imperfect information. We present a novel
three-valued semantics for
ATL
∗
, respectively
ATL
, under
bounded recall and imperfect information, and study the cor-
responding model checking problems. Most importantly, we
show that the three-valued semantics constitutes an approxi-
mation with respect to the traditional two-valued semantics.
In the light of this we construct a sound, albeit partial, al-
gorithm for model checking two-valued perfect recall via its
approximation as three-valued bounded recall.
Date Acceptance
2018-07-12
Publisher
Association for the Advancement of Artificial Intelligence
Copyright Statement
© 2018, Association for the Advancement of Artificial
Intelligence (www.aaai.org). All rights reserved.
Intelligence (www.aaai.org). All rights reserved.
Sponsor
Royal Academy Of Engineering
Grant Number
CIET 1718/26
Source
16th International Conference on Principles of Knowledge Representation and Reasoning
Publication Status
Accepted
Start Date
2018-10-27
Finish Date
2018-11-02
Coverage Spatial
Tempe, Arizona, USA