Responsibility Attribution in Parameterized Markovian Models
Authors: Christel Baier, Florian Funke, Rupak Majumdar11734-11743
AAAI 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | Our main technical result is an algorithm for deciding if a path-based attribution scheme for a rational (ratios of polynomials) cost function is over a rational threshold. In particular, it is decidable if the Aumann-Shapley value for a player is at least a given rational number. As a consequence, we show that responsibility attribution is decidable for parametric Markov chains and for a general class of properties that include expectation and variance of discounted sum and long-run average rewards, as well as specifications in temporal logic. |
| Researcher Affiliation | Academia | 1Technische Universit at Dresden, Dresden, Germany 2MPI-SWS, Kaiserslautern, Germany {christel.baier, florian.funke}@tu-dresden.de, rupak@mpi-sws.org |
| Pseudocode | No | The paper describes algorithms conceptually and refers to mathematical proofs, but does not include structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described. |
| Open Datasets | No | The paper is theoretical and does not use or refer to publicly available datasets for training, validation, or testing. |
| Dataset Splits | No | The paper is theoretical and does not involve dataset splits for training, validation, or testing. |
| Hardware Specification | No | The paper does not provide specific hardware details used for running its theoretical computations or examples. |
| Software Dependencies | No | The paper does not provide specific ancillary software details with version numbers needed to replicate any computational aspects. |
| Experiment Setup | No | The paper is theoretical and does not describe an experimental setup with hyperparameters or training configurations. |