Welcome! The whole workshop will be held in gather.town. Please drop in any time.

I consider the sorts of models people construct to reason about other people’s thoughts based on several strands of evidence from cognitive science experiments. The first is from studies of how people think about decisions to cooperate or not with another person in various sorts of social interactions in which they must weigh their own self-interest against the common interest. I discuss results from well-known games such as the Prisoner’s dilemma, such as the finding that people who took part in the game imagine the outcome would have been different if a different decision had been made by the other player, not themselves. The second strand of evidence comes from studies of how people think about other people’s false beliefs. I discuss reasoning in change-of-intentions tasks, in which an observer who witnesses an actor carrying out an action forms a false belief about the reason. People appear to develop the skills to make inferences about other people’s false beliefs by creating counterfactual alternatives to reality about how things would have been. I consider how people construct models of other people’s thoughts, and consider the implications for how AI agents could construct models of other AI agents.

Explanation of the Game Rules for the live coding session

Find your group

Time for your team to solve the game. Session will be held in gather.town

Will be held in gather.town

The matches between the teams will be shown live during the lunch break. Optional attendance.

Short presentation of which strategies seemed to work well. No thorough analysis yet.

I will look at some of the often unstated principles common in multiagent learning research (and emergent communication work too), suggesting that they may be responsible for holding us back. In response, I will offer an alternative set of principles, which leads to the view of hindsight rationality, with connections to online learning and correlated equilibria. I will then describe some recent technical work understanding how we can build increasingly more powerful algorithms for hindsight rationality in sequential decision-making settings.

Speaker's Bio: Michael Bowling is a professor at the University of Alberta, a Fellow of the Alberta Machine Intelligence Institute, and a senior scientist in DeepMind. Michael led the Computer Poker Research Group, which built some of the best poker playing artificial intelligence programs in the world, including being the first to beat professional players at both limit and no-limit variants of the game. He also was behind the use of Atari 2600 games to evaluate the general competency of reinforcement learning algorithms and popularized research in Hanabi, a game that illustrates emergent communication and theory of mind.

I claim that human languages can be modeled as information-theoretic codes, that is, systems that maximize information transfer under certain constraints. I argue that the relevant constraints for human language are those involving the cognitive resources used during language production and comprehension and in particular working memory resources. Viewing human language in this way, it is possible to derive and test new quantitative predictions about the statistical, syntactic, and morphemic structure of human languages. I start by reviewing some of the many ways that natural languages differ from optimal codes as studied in information theory. I argue that one distinguishing characteristic of human languages, as opposed to other natural and artificial codes, is a property I call information locality: information about particular aspects of meaning is localized in time within a linguistic utterance. I give evidence for information locality at multiple levels of linguistic structure, including the structure of words and the order of words in sentences. Next, I state a theorem showing that information locality is an inevitable property of any communication system where the encoder and/or decoder are operating under memory constraints. The theorem yields a new, fully formal, and quantifiable definition of information locality, which leads to new predictions about word order and the structure of words across languages. I test these predictions in broad corpus studies of word order in over 50 languages, and in case studies of the order of morphemes within words in two languages.

Will be held in gather.town

We will chat about the game and our insights into the problem of zero-shot coordination after playing it.

In this panel, we want to discuss the lessons we learned in this workshop about the possibilities and necessities of learning to cooperate and communicate with strangers.

Guests: Angeliki Lazaridou Jakob Foerster Ruth Byrne Michael Bowling Richard Futrell

Come together to discuss the workshop in our cozy gather.town bar