Showing papers on "Counterfactual conditional published in 1996"

Counterfactual Thought Experiments in World Politics Logical, Methodological, and Psychological Perspectives

Abstract: List of ContributorsAcknowledgments1Counterfactual Thought Experiments in World Politics: Logical, Methodological, and Psychological Perspectives12Causes and Counterfactuals in Social Science: Exploring an Analogy between Cellular Automata and Historical Processes393Counterfactual Reasoning in Western Studies of Soviet Politics and Foreign Relations694Confronting Hitler and Its Consequences955Back to the Past: Counterfactuals and the Cuban Missile Crisis1196Counterfactual Reasoning in Motivational Analysis: U.S. Policy toward Iran1497Counterfactuals about War and Its Absence1718Using Counterfactuals in Historical Analysis: Theories of Revolution1879Counterfactuals and International Affairs: Some Insights from Game Theory21110Off-the-Path Behavior: A Game-Theoretic Approach to Counterfactuals and Its Implications for Political and Historical Analysis23011Rerunning History: Counterfactual Simulation in World Politics24712Counterfactuals, Past and Future268Commentary 1: Conceptual Blending and Counterfactual Argument in the Social and Behavioral Sciences291Commentary 2: Psychological Biases in Counterfactual Thought Experiments296Commentary 3: Counterfactual Inferences as Instances of Statistical Inferences301Commentary 4: Counterfactuals, Causation, and Complexity309References317Index337

Knowledge, Belief and Counterfactual Reasoning in Games

Abstract: Deliberation about what to do in any context requires reasoning about what will or would happen in various alternative situations, including situations that the agent knows will never in fact be realized. In contexts that involve two or more agents who have to take account of each others’ deliberation, the counterfactual reasoning may become quite complex. When I deliberate, I have to consider not only what the causal effects would be of alternative choices that I might make, but also what other agents might believe about the potential effects of my choices, and how their alternative possible actions might affect my beliefs. Counter factual possibilities are implicit in the models that game theorists and decision theorists have developed – in the alternative branches in the trees that model extensive form games and the different cells of the matrices of strategic form representations – but much of the reasoning about those possibilities remains in the informal commentary on and motivation for the models developed. Puzzlement is sometimes expressed by game theorists about the relevance of what happens in a game ‘off the equilibrium path’: of what would happen if what is (according to the theory) both true and known by the players to be true were instead false. My aim in this paper is to make some suggestions for clarifying some of the concepts involved in counterfactual reasoning in strategic contexts, both the reasoning of the rational agents being modeled, and the reasoning of the theorist who is doing the modeling, and to bring together some ideas and technical tools developed by philosophers and logicians that I think might be relevant to the analysis of strategic reasoning, and more generally to the conceptual foundations of game theory.

Antecedents to Spontaneous Counterfactual Thinking: Effects of Expectancy Violation and Outcome Valence

Abstract: Three studies examined the effects of expectancy violation and outcome valence on spontaneous counterfactual thinking. In Study 1, prior expectations and outcome valence were varied orthogonally in a vignette. More counterfactuals were generated after failures and unexpected outcomes. Also, more additive than subtractive counterfatuals were found after failure, particularly unexpected failure, and more subtractive than additive counterfactuals were found after unexpected success. Evidence for the generality of these results was obtained in Study 2, in which counterfactuals were assessed after students' real-life exam performances. In Study 3, the authors further assessed nonspontaneous counterfactuals, which were shown to differ in number and structure from spontaneous counterfactuals. Discussion centers around antecedents to spontaneous counterfactual thinking and comparisons to research on spontaneous causal attributions.

Counterfactual thinking and ascriptions of cause and preventability.

Abstract: Research suggests that counterfactuals (i.e., thoughts of how things might have been different) play an important role in determining the perceived cause of a target outcome. Results from 3 scenario studies indicate that counterfactual content overlapped primarily with thoughts of how an outcome might have been prevented (preventability ascriptions) rather than with thoughts of how it might have been caused (causal ascriptions). Counterfactuals and preventability ascriptions focused mainly on controllable antecedents, whereas causal ascriptions focused mainly on antecedents that covaried with the target outcome over a focal set of instances. Contrary to current theorizing, causal ascriptions were unrelated to counterfactual content (Study 3). Results indicate that the primary criterion used to recruit causal ascriptions (covariation) differs from that used to recruit counterfactuals (controllability).

Conditionals: from philosophy to computer science

Abstract: 1. Introduction 2. The emperor's new clothes: some recurring problems in the formal analysis of counterfactuals 3. A unified view of consequence relation, belief revision, and conditional logic 4. Defeasible logics: demarcation and affinities 5. Commonsense entailment: a conditional logic for some generics 6. The Ramsey test revisited 7. Epistemic conditionals, snakes and stars 8. Conditional action 9. Of the revision of conditional belief sets 10. Conditional objects, possibility theory and default roles 11. Conditional implications and non-monotonic consequence

Probabilistic counterfactuals: semantics, computation, and applications

Abstract: Counterfactual conditionals of the form "If A were true, then C" are commonly used to express generic, law-like relationships. This dissertation provides formal semantics for interpreting such conditionals, as well as computational methods for answering queries of the form "Find the probability of C if A were true, given that A is in fact false." Here, generic knowledge is represented as a network of causal relationships among variables of interest, while specific occurrences are represented as instantiations of those variables. The counterfactual antecedent A is interpreted as a local, hypothetical change induced by forces external to the system. Counterfactual probabilities are computed using standard evidence propagation in two loosely coupled Bayesian networks--one corresponding to the factual world, the other to the counterfactual--where the probabilities are defined over the causal mechanisms governing the domain. When such probabilities are not available, we develop methods for computing either bounds on the counterfactual probabilities or qualitative beliefs, i.e., order-of-magnitude abstractions of standard probabilities. We then demonstrate the usefulness of our formulation in application areas where counterfactual reasoning is essential but considered difficult, if not impossible, to compute. First, we examine experimental studies in which subjects do not comply perfectly with treatment assignment, thus violating the tenets of randomized experimentation. We show that it is possible in such studies to derive informative bounds on treatment efficacy, tighter than any yet reported in the statistical or the epidemiological literature. Next, we address the problem of determining legal responsibility (e.g., whether the defendant is liable for the plaintiff's injuries). Although counterfactual assertions in this domain cannot be evaluated using conventional statistical analysis, under our formalism they can be assigned meaningful probability intervals. In the areas of econometrics and the social sciences, the formalism allows coherent evaluation of policies involving the control of variables that, prior to enacting a given policy, were influenced by other variables in the system. Finally, in the area of artificial intelligence, the formulation provides a computational model for interpreting counterfactual utterances, answering counterfactual queries, and evaluating actions and plans.

The Role of Counterfactual Thinking in Reasoning

Abstract: Counterfactual generation is an important part of reasoning. Both the judgment of events and affective reactions to those events depend not only on the events themselves, but on counterfactual alternatives to those events. Counterfactual thinking serves several positive functions. However, there are also dysfunctional aspects. First, judgments of general versus specific instances are often inconsistent, and this leads to problematic, irrational decisions. We explain these inconsistencies by suggesting that specific instances easily afford counterfactuals, and are judged in the context of these counterfactuals. Alternatively, general cases are evaluated in terms of quite different contrast cases, global expectations. Second, in assigning blame for the negative outcome of a chain of events, people assign too much causality to recent events. Our explanation is that these recent events are most accessible and are most likely to be mutated in the course of counterfactual generation. Such mutability is important in causal assignment. © 1997 John Wiley & Sons, Ltd.

The Complexity of Nested Counterfactuals and Iterated Knowledge Base Revisions

Abstract: We consider the computational complexity of evaluating nested counterfactuals over a propositional knowledge base. A counterfactualpqis a conditional query with the meaning “Ifpwould be true in the knowledge base, would it then hold that alsoqis true,” which is different from material implicationp?q. A nested counterfactual is a counterfactual statement where the premisepor the conclusionqis a counterfactual. Statements of the formp1>(p2?(pnq)?) intuitively correspond to conditional queries involving a sequence of revisions. We show that evaluating such statements is?P2-complete and that this task becomes PSPACE-complete if negation is allowed in a nesting of this form. We also consider nesting a counterfactual in the premise, i.e., (pq)>r, and show that evaluating such statements is?P4-complete, thus most likely much harder than evaluatingp>(qr). Finally, we also address iterated nestings in the premise and the mix of nestings in the premise and the conclusion.

Is There Superluminal Causation in Relativistic Quantum Field Theory

Abstract: The aim of this paper is to propose a counterfactual analysis of the problem of causal dependence between spacelike separated events — as these events are described in the operator algebraic framework of relativistic quantum field theory (Haag 1992, Horuzhy 1990). The analysis is based on Lewis’ (1986) idea of counterfactual chancy causation and shall employ Stalnaker’s possible worlds semantics for counterfactuals.

Stretched Lines, Averted Leaps, and Excluded Competition: A Theory of Scientific Counterfactuals

Abstract: Lewis' argument against the Limit Assumption and Pollock's Generalized Consequence Principle together suggest that "minimal-change" theories of counterfactuals are wrong. The "small-change" theories presented by Nute do not say enough. While these theories rely on closeness between possible worlds, I base an alternative on the ceteris paribus concept. My theory solves a problem that the above cannot, and is more relevant to the philosophy of science. Ceteris paribus conditions should normally include the causes, but exclude the effects, of the negated antecedent. An example from community ecology, the debate over null models in island-biogeographical studies of competition, supports these arguments.

Counterfactuals and updates as inverse modalities: preliminary version

Abstract: We point out a simple but hitherto ignored link between the theory of updates and counterfactuals and classical modal logic: update is a classical existential modality, counterfactual is a classical universal modality, and the link between the two (called the Ramsey rule) is simply the link between two inverse accessibility relations of a classical Kripke model.

Using Computational Methods to Perform Counterfactual Analyses of Formal Theories

Abstract: Recently there has been an increase in the number of researchers who use rational choice models to explain single cases and rare events. Because of the small number of cases under study, these researchers must rely either explicitly or implicitly on counterfactual reasoning. This paper argues that computational methods provide a profitable means of carrying out rigorous counterfactual analysis. The authors advocate robustness analysis as one important part of the counterfactual analysis of formal theories. Specifically, they evaluate the robustness of the behavioral assumptions of two formal models using various heuristic search algorithms and Markov chains. They find that Kuran's (1989) threshold model of mass protest and Ingberman's (1985) model of direct-democracy referenda are robust to perturbations in their behavioral assumptions. These findings increase the plausibility of causal claims made by scholars who use these models to explain specific events.