The complexity of optimization problems
Journal of Computer and System Sciences - Structure in Complexity Theory Conference, June 2-5, 1986
A catalog of complexity classes
Handbook of theoretical computer science (vol. A)
Computing functions with parallel queries to NP
Theoretical Computer Science
On the complexity of unique solutions
Journal of the ACM (JACM)
Causality: models, reasoning, and inference
Causality: models, reasoning, and inference
The Art of Causal Conjecture
Complexity results for structure-based causality
Artificial Intelligence
Causes and explanations in the structural-model approach
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Social causality and responsibility: modeling and evaluation
Lecture Notes in Computer Science
Evaluating a computational model of social causality and responsibility
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
What causes a system to satisfy a specification?
ACM Transactions on Computational Logic (TOCL)
International Journal of Artificial Intelligence in Education
Formal Methods in System Design
Causes and explanations in the structural-model approach: Tractable cases
Artificial Intelligence
Efficient automatic STE refinement using responsibility
TACAS'08/ETAPS'08 Proceedings of the Theory and practice of software, 14th international conference on Tools and algorithms for the construction and analysis of systems
The complexity of causality and responsibility for query answers and non-answers
Proceedings of the VLDB Endowment
A logic for reasoning about counterfactual emotions
Artificial Intelligence
Tracing data errors with view-conditioned causality
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
The face of emotions: a logical formalization of expressive speech acts
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
Causality, responsibility, and blame: a structural-model approach
SUM'11 Proceedings of the 5th international conference on Scalable uncertainty management
An Ensemble Architecture for Learning Complex Problem-Solving Techniques from Demonstration
ACM Transactions on Intelligent Systems and Technology (TIST)
LEARNING AND VERIFYING SAFETY CONSTRAINTS FOR PLANNERS IN A KNOWLEDGE-IMPOVERISHED SYSTEM
Computational Intelligence
Modeling social causality and responsibility judgment in multi-agent interactions
Journal of Artificial Intelligence Research
Finding optimal Bayesian networks using precedence constraints
The Journal of Machine Learning Research
Causality and responsibility: probabilistic queries revisited in uncertain databases
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Modeling social causality and responsibility judgment in multi-agent interactions: extended abstract
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Accountability and Q-Accountable Logging in Wireless Networks
Wireless Personal Communications: An International Journal
| Hi-index | 0.00 |
Causality is typically treated an all-or-nothing concept; either A is a cause of B or it is not. We extend the definition of causality introduced by Halpern and Pearl (2004a) to take into account the degree of responsibility of A for B. For example, if someone wins an election 11-0, then each person who votes for him is less responsible for the victory than if he had won 6-5. We then define a notion of degree of blame, which takes into account an agent's epistemic state. Roughly speaking, the degree of blame of A for B is the expected degree of responsibility of A for B, taken over the epistemic state of an agent.