Epistemic Disturbance in the Graph Model for Conflict Resolution: State-Preserving Actions, Four-Valued Assessments, and the Distinction between Capability and Intention
Building on a four-valued extension of GMCR from the author's earlier work, which separates evidence for and against, we show that evidence for a move can only enable perceived moves and evidence against can only disable them, that two of the four reduction operators ignore one kind of evidence, and that contradictory assessments are absorbing under monotone accumulation.
ProofPaper ↗
Key points
- In the graph model for conflict resolution (GMCR), a decision maker (DM) either moves the conflict to another state or does nothing.
- We introduce such state-preserving actions by augmenting states with the DMs' epistemic states: a physical move changes the physical state, a state-preserving action changes only the epistemic state, and inaction is the absence of a transition.
- Actions generate evidence through observer-specific interpretation maps.
- Capability assessments affect all sanction-based stability concepts, and on the DM's own side also Nash stability, whereas intention assessments affect only sequential stability.
Sources (1)
- [1]Epistemic Disturbance in the Graph Model for Conflict Resolution: State-Preserving Actions, Four-Valued Assessments, and the Distinction between Capability and IntentionarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 8, 11:00 AM
Building on a four-valued extension of GMCR from the author's earlier work, which separates evidence for and against, we show that evidence for a move can only enable perceived moves and evidence against can only disable them, that two of the four reduction operators ignore one kind of evidence, and that contradictory assessments are absorbing under monotone accumulation.
In the graph model for conflict resolution (GMCR), a decision maker (DM) either moves the conflict to another state or does nothing.
Extractive summary: sentences quoted from the sources.
