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Models of Morality, Morality of Models

March 6-7, 2020
Carnegie Mellon University (Adamson Wing, Baker Hall)
This workshop is free to attend. 

Organizers: David Danks, Kevin Kelly, Simon Cullen

Recent years have seen an explosion of research into the empirical bases of human moral judgment along with a corresponding interest in formal and computational models of human morality. At the same time, AI and robotics researchers aim to develop systems that are themselves capable of moral judgment, and so require some model of morality. With this workshop, we hope to spur new and generative  collaborations between researchers pursuing these two parallel lines of inquiry.

Confirmed Speakers:

Logic, Information, and Topology Workshop

Saturday, October 20th, 2018 - 9-6pm
Baker Hall 136A - Adamson Wing

Dynamic epistemic logic concerns the information conveyed by the beliefs of other agents.  Belief revision theory studies rational belief change in light of new information. Formal learning theory concerns systems that learn the truth on increasing information. Topology is emerging as a particularly apt formal perspective on the underlying concept of propositional information.  The talks in this workshop address the preceding themes from a range of overlapping perspectives.

Workshop on Foundations of Causal Discovery

September 22-23, 2018
Baker Hall A53 Steinberg Auditorium

This workshop is open to the public and brings together experts from philosophy, statistics, and machine learning, to shed fresh light on the special epistemological issues occasioned by causal discovery from non-experimental data.

View photos from the workshop

Attitudes and Questions Workshop

June 10 and 11, 2016 - Center for Formal Epistemology

Question embedding in natural language allows a subject to be related to a question by either a (traditionally) propositional attitude like knowledge and forgetting, or an (apparently) inherently question-oriented predicate like asking or wondering. Attitudes held of questions are an important locus of research into the semantics of both interrogative clauses and clause-embedding verbs, closely connected with the notion of the answerhood conditions of a question, and with the operations of composition involved in combining these types of predicates with semantically heterogeneous arguments. The attitudes that relate us to questions are also of considerable epistemic interest, touching on the nature of the knowledge relation and on the way that questions structure our inquiries. This workshop aims to bring together a diverse group of experts on the semantics and epistemic issues raised by these phenomena, to promote exchange of theoretical perspectives and approaches, and to help to move forward current work on questions and attitudes.

Workshop Schedule

Workshop Speakers:

Jane Friedman

New York University

Yimei Xiang 

Harvard University 

Carlotta Pavese 

Duke University 

Danny Fox 

Massachusetts Institute of Technology

Alexandre Cremers 

École Normale Supérieure,
Laboratoire de Sciences Cognitives et Psycholinguistique (LSCP)

Benjamin Spector

Institut Jean Nicod & Ecole Normale Supérieure

Konstantin Genin

Carnegie Mellon University 

B. R. George

Carnegie Mellon University
"Differentiating Contents" CFE/Linguistics Workshop

Saturday, December 5, 2015 - Carnegie Mellon, Baker Hall, Dean’s Conference Room, 154R

A variety of phenomena have motivated researchers to distinguish between different types of linguistic content. One classical distinction is that made by Austin (1962) and Searle (1969) between the propositional content of utterances and their speech act force. Another classical distinction is that between assertoric and presupposed content (Frege 1893, Strawson 1950, Stalnaker 1974, inter alia). In recent years, a new distinction between at-issue and not at-issue content (Potts 2005, Simons et al. 2010) has been introduced, to some extent offered as a replacement for the asserted/presupposed distinction. One empirical domain where the at-issue/not at-issue distinction has been utilized by some researchers is in the study of evidentials, a category of linguistic forms which provide information about the speaker’s evidential relation to the (remaining) content of her utterance.

This one day workshop will bring together researchers with intersecting work on the nature of these distinctions, on the empirical evidence for them, and on how to model them.

Workshop Schedule

TARK 2015

The Fifteenth conference on Theoretical Aspects of Rationality and Knowledge was held at Carnegie Mellon University from June 4-6, 2015.

Workshop on Epistemology, Logic, and Games

December 3, 2014, at Baker Hall 150, Carnegie Mellon University

Abstracts

Joseph Y. Halpern: Game Theory With Translucent Players

Abstract: A traditional assumption in game theory is that players are opaque to one another - if a player changes strategies, then this change in strategies does not affect the choice of other players' strategies. In many situations this is an unrealistic assumption. We develop a framework for reasoning about games where the players may be translucent to one another; in particular, a player may believe that if she were to change strategies, then the other player would also change strategies. I show that by assuming translucent players, we can recover many of the regularities observed in human behavior in well-studied games such as Prisoner's Dilemma, Traveler's Dilemma, Bertrand Competition, and the Public Goods game. I then consider solution concepts appropriate for translucent players. I characterize the analogues of rationalizability and Nash equilibrium for translucent players. The former is in terms of an analogue of common belief of rationality: Common Counterfactual Belief of Rationality (CCBR) holds if (1) everyone is rational, (2) everyone counterfactually believes that everyone else would still be rational even if i were to switch strategies), (3) everyone counterfactually believes that everyone else is rational, and counterfactually believes that everyone else is rational, and so on. CCBR characterizes the set of strategies surviving iterated removal of minimax-dominated strategies, where a strategy s for playeriis minimax dominated bys'if the worst-case payoff foriusings'is better than the best possible payoff usings.

This first part of the talk represents joint work with Valerio Capraro; the second part represents joint work with Rafael Pass.

Adam Bjorndahl:Types and Intention (joint with Joseph Y. Halpern and Rafael Pass)

Abstract:Type spaces were introduced by John Harsanyi as a formal mechanism for modeling games of incomplete information. In particular, in a Bayesian game types encode payoff-relevant information, a typical example being how each participant values the items in an auction. On the other hand, type spaces have also been co-opted for the epistemic analysis of games of complete information: in this context, types serve as modeling tools that provide a succinct representation of the players' hierarchical beliefs.

One might wonder whether these two applications can work in combination: in a Bayesian game, can the players' (hierarchical) beliefs themselves count as payoff-relevant characteristics? The answer to this question is no for a wide class of beliefs (specifically, all beliefs about strategies); however, we show that by generalizing the classical setting to distinguish between two notions of strategy - what we call "intended" versus "actual" strategies - this limitation can be circumvented. The resulting class of models is flexible enough to capture psychological games (in which preferences can depend on feelings like guilt or surprise), and provides a natural setting in which to endogenize the reference point that figures centrally in prospect theory. Moreover, under the plausible assumption that, in equilibrium, intended and actual strategies line up, we show that equilibria do not exist in general, and establish conditions for existence in terms of the richness of the associated type space.

Russell Golman: Curiosity, Information Gaps, and the Utility of Knowledge (including applications to risk and ambiguity) (joint with George Loewenstein)

Abstract: We propose an integrated theoretical framework that captures the diverse motives driving the preference to obtain or avoid information. Beyond the conventional desire for information as an input to decision making, people are driven by curiosity, which is a desire for knowledge for its own sake, even in the absence of material benefits, and people are additionally motivated to seek out information about issues they like thinking about and avoid information about issues they do not like thinking about (an ostrich effect). The standard economic framework is enriched with the insights that knowledge has valence, that ceteris paribus people want to fill in information gaps, and that, beyond contributing to knowledge, information affects the focus of attention. We then apply our model to the domain of decision making under uncertainty. An uncertain prospect exposes an individual to an information gap. Gambling makes the missing information more important, attracting more attention to the information gap. To the extent that the uncertainty (or other circumstances) makes the information gap unpleasant to think about, an individual tends to be averse to risk and ambiguity. Yet when an information gap happens to be pleasant, an individual may seek gambles providing exposure to it. The model provides explanations for source preference regarding uncertainty, the comparative ignorance effect under conditions of ambiguity, aversion to compound risk, and more.

Kevin T. Kelly: A Learning Semantics for Inductive Knowledge

Abstract: Possible world semantics is supposed to be non-committal about the nature of knowledge - the accessible worlds are possible for all one knows. But as soon as one adds operators for incoming information (e.g., public announcement), the accessible worlds are possible for all one has been informed, which implies inductive skepticism - the view that one can know nothing that extends one's current information. Possible world semantics also implies, notoriously, that knowledge is consistent and closed under logical consequence. I will present a semantics for inductive knowledge, in which time and learning in response to new information are represented explicitly in terms of Turing machines that process sequences of inputs. Based on the semantics, I will explain (i) how S4 is right and S5 is wrong, (ii) how inductive knowledge is close-able (but not closed) under deductive consequence, (iii) how one can know that p and not know that q, even though p and q are logically equivalent, (iv) how it is possible to convey inductive knowledge (rather than mere, true belief), and (v) how a group can come to common knowledge of rationality (or irrationality) just by watching one another's play in ever-longer centipede games.

Workshop on Simplicity and Causal Discovery

June 6-8, 2014, at Carnegie Mellon University

Rationale: Correlation does not imply causation---earthquakes are correlated with structural cracks, but filling the cracks does not prevent earthquakes. However, Patterns of non-experimental, empirical dependence can point toward causation and modern computing power can be harnessed to search such patterns for networks of causal relations. The idea goes back to Spearman, but the past three decades have seen a proliferation of promising, alternative approaches, based on Tetrad equations, the i-map order, independent component analysis, and information theory. One common theme that runs through all of these approaches is a heavy reliance on Ockham's razor, the characteristic scientific bias toward simpler, more unified, or more explanatory theories. That raises foundational questions. How is Ockhams razor applied in causal inference? What is the underlying notion of simplicity? What justifies the assumption that the causal truth is simple? The aim of this workshop is to bring together top researchers in the area for a candid, foundational discussion of those and related questions.

The workshop is sponsored by a generous grant from the John Templeton Foundation.

Third CSLI Workshop on Logic, Rationality and Interaction

May 31-June 1, 2014, Cordura Hall, CSLI, Stanford University

The CFE is co-sponsoring the Third CSLI Workshop on Logic, Rationality and Interaction.

Modal Logic Workshop: Consistency and Structure

Venue

8:30 AM, Saturday, April 12, 2014, Wean Hall 4625, Carnegie Mellon University.

Schedule:

8:30-9:00 Bagels and coffee

Session I: Consistency

9:00-10:30 The Paradox of the Two Firemen
J. Michael Dunn, School of Informatics & Computing, and Dept. of Philosophy, Indiana University Bloomington

10:45-12:00 Clean Epistemic Principles from Messy Belief
Kevin T. Kelly, Dept. of Philosophy, Carnegie Mellon University

12:00-2:00 Lunch

Session II: Structure:

2:00-3:30 Partiality and Adjointness in Modal Logic,
Wesley Holliday, Dept. of Philosophy, University of California, Berkeley

3:45-5:00 Topos theoretic semantics for higher-order modal logic
Steven Awodey, Dept. of Philosophy, Carnegie Mellon University.

5:00-6:30 Topological Semantics for Provability Logics
Thomas Icard, Herbert Simon Postdoctoral Fellow, Carnegie Mellon University, Department of Philosophy, Stanford Univesity.

Workshop: Case Studies of Causal Discovery with Model Search

October 25-27, 2013

General Information

The Case Studies of Causal Discovery with Model Search Workshop is focused on applications of causal model search to science. It will include sessions on model search in Genetics, Biology, fMRI, Educational Research, Economics, and other disciplines.

Dates: October 25-27, 2013 (Friday-Sunday)
Location: Carnegie Mellon University, Pittsburgh, PA
The Friday sessions will take place in Rangos Hall (2nd floor, University Center)
The Saturday and Sunday sessions will take place in Baker Hall A53

Workshop Topic:
Computer scientists, statisticians, and philosophers have created a precise mathematical framework for representing causal systems called "Graphical Causal Models." This framework has supported the rigorous description of causal model spaces and the notion of empirical indistinguishability/equivalence within such spaces, which has in turn enabled computer scientists to develop asymptotically reliable model search algorithms for efficiently searching these spaces. The conditions under which these methods are practically useful in applied science is the topic of this workshop. The workshop will bring together scholars from genetics, biology, economics, fMRI-based cognitive neuroscience, climate research, education research, and several other disciplines, all of whom have successfully applied computerized search for causal models toward a scientifically challenging problem. The goals for the workshop are to: (1) to identify strategies for applying causal model search to diverse domain-specific scientific questions; (2) to identify and discuss methodological challenges that arise when applying causal model search to real-world scientific problems; and (3) to take concrete steps toward creating an interdisciplinary community of researchers interested in applied causal model search. We welcome junior scholars and graduate students, and we will host a free introductory tutorial on model search the first morning of the workshop.

Confirmed Speakers:

David Bessler (Economics, Texas A&M)
Frederick Eberhardt (Philosophy, Cal Tech)
Imme Ebert-Uphoff (Electrical & Computer Engineering, Colorado State University)
Kathleen Gates (Quantitative Psychology, University of North Carolina)
Clark Glymour (Philosophy, CMU)
Isabelle Guyon (Clopinet, Berkeley, CA)
Catherine Hanson (Psychology, Rutgers University)
Kevin Hoover (Economics and Philosophy, Duke University)
Marloes Maathuis (Statistics, ETH Zurich)
Alessio Moneta (Economics, Scuola Superiore Sant'Anna)
Sergey Plis (Mind Research Network and University of New Mexico)
Joseph Ramsey (Philosophy, CMU)
Martina Rau (Learning Sciences, Univ. of Wisconsin, Madison)
Richard Scheines (Philosophy, CMU)
Cosma Shalizi (Statistics, CMU)
Bill Shipley (Biology, Sherbrooke University)
Alexander Statnikov (Health Informatics and Bioinformatics, New York University)
Ioannis Tsamardinos (Computer Science, University of Crete)

Workshop on the Logic of Simplicity

June 7-9 2013

CFE/Studia Logica

Rationale: Ockham's razor is the characteristic bias toward simple hypotheses that has characterized scientific inquiry since Copernicus.  But what is it, exactly?  This workshop aims to revisit that question from a fresh logical perspective.  Potential candidates for the simplicity order include dimensionality, Kolmogorov complexity, and VC dimension.  Candidates for Ockham's razor, itself, include logical theories for revising belief in light of such an order in the deterministic case and a host of model selection methods on the side of statistics and machine learning.   This interdisciplinary workshop will begin to explore a number of new and interesting logical questions at the interface of logic and scientific method.  Which orders are simplicity orders?   Is simplicity relative to questions or subject to other framing effects?  How should a simplicity order be modified in light of new information?  What may one believe in light of a simplicity order and given information?  What should one do if the simplicity order branches?   Are the essential features of a simplicity order preserved by the associated belief revision rule?  Are standard belief revision principles descriptively plausible in scientific applications?  Is simplicity absolute or relative to framing effects?  Is there any normative reason to revise according to simplicity rather than some other principle?  Addressing these fundamental questions promises both to sharpen our conception of scientific method and to broaden our ideas about the logic of belief revision.

2nd Conference on Games, Interactive Rationality, and Learning (GIRL)

April 23-26, 2013

Lund, Sweden

Cosponsored by the CFE

Workshop on Cognition and Formal Theories of Reasoning

March 30, 2013

CFE
Niki Pfeifer (LMU & CFE Visiting Fellow)How People (Ought to) Reason under Uncertainty
Hanti Lin and Kevin T. Kelly (CMU Philosophy)Propositional Beliefs that Aptly Represent Subjective Probabilities in Light of New Information
Wilfried Sieg (CMU Philosophy)Structural Proof Theory: Uncovering Capacities of the Mathematical Mind?
Chris Lucas (CMU Psychology)Bayes net Models of Counterfactual Reasoning
Charles Kemp and Chris Carroll (CMU Psychology)Hypothesis Space Checking in Everyday Reasoning
David Danks(CMU Philosophy)Discussion: Logic, Psychology, and Reasoning"

"Evolution, Learning, and Games"

October 6, 2012

CFE

8:45 Introduction
9:00 Simon Huttegger (UC Irvine) Probe and Adjust
10:30 Brian Skyrms (UC Irvine) Learning Signaling Chains
12:00 Lunch
2:00 Rory Smead (Northeastern University) Two Evolutionary Models of Unconditional Spite
3:30 Russell Golman (Carnegie Mellon University) Basis of Attraction and Equilibrium Selection with Population Learning Dynamics
5:00 Final Thoughts