Extended Goal Recognition: Lessons from Magic.

The "science of magic" has lately emerged as a new field of study, providing valuable insights into the nature of human perception and cognition. While most of us think of magic as being all about deception and perceptual "tricks", the craft-as documented by psychologists and professional magicians-provides a rare practical demonstration and understanding of goal recognition. For the purposes of human-aware planning, goal recognition involves predicting what a human observer is most likely to understand from a sequence of actions.

Norm talk and human cooperation: Can we talk ourselves into cooperation?

Norm talk is verbal communication that explicitly states or implicitly implies a social norm. To investigate its ability to shape cultural dynamics, 2 types of norm talk were examined: injunction, which explicitly states what should be done, and gossip, which implies a norm by stating an action approved or disapproved of by the communicator. In 2 experiments, participants engaged in norm talk in repeated public goods games.

Sustainability is possible despite greed - Exploring the nexus between profitability and sustainability in common pool resource systems.

The sustainable use of common pool resources has become a significant global challenge. It is now widely accepted that specific mechanisms such as community-based management strategies, institutional responses such as resource privatization, information availability and emergent social norms can be used to constrain individual 'harvesting' to socially optimal levels. However, there is a paucity of research focused specifically on aligning profitability and sustainability goals.

Culture and cooperation in a spatial public goods game.

We study the coevolution of culture and cooperation by combining the Axelrod model of cultural dissemination with a spatial public goods game, incorporating both noise and social influence. Both participation and cooperation in public goods games are conditional on cultural similarity. We find that a larger "scope of cultural possibilities" in the model leads to the survival of cooperation, when noise is not present, and a higher probability of a multicultural state evolving, for low noise rates.

Diversity and Community Can Coexist.

We examine the (in)compatibility of diversity and sense of community by means of agent-based models based on the well-known Schelling model of residential segregation and Axelrod model of cultural dissemination. We find that diversity and highly clustered social networks, on the assumptions of social tie formation based on spatial proximity and homophily, are incompatible when agent features are immutable, and this holds even for multiple independent features. We include both mutable and immutable features into a model that integrates Schelling and Axelrod models, and we find that even for multiple independent features, diversity and highly clustered social networks can be incompatible on the assumptions of social tie formation based on spatial proximity and homophily.

Dilemma of dilemmas: how collective and individual perspectives can clarify the size dilemma in voluntary linear public goods dilemmas.

Empirical findings on public goods dilemmas indicate an unresolved dilemma: that increasing size-the number of people in the dilemma-sometimes increases, decreases, or does not influence cooperation. We clarify this dilemma by first classifying public goods dilemma properties that specify individual outcomes as individual properties (e.g.

Ultrametric distribution of culture vectors in an extended Axelrod model of cultural dissemination.

The Axelrod model of cultural diffusion is an apparently simple model that is capable of complex behaviour. A recent work used a real-world dataset of opinions as initial conditions, demonstrating the effects of the ultrametric distribution of empirical opinion vectors in promoting cultural diversity in the model. Here we quantify the degree of ultrametricity of the initial culture vectors and investigate the effect of varying degrees of ultrametricity on the absorbing state of both a simple and extended model.

Incorporating feature ranking and evolutionary methods for the classification of high-dimensional DNA microarray gene expression data.

Background: DNA microarray gene expression classification poses a challenging task to the machine learning domain. Typically, the dimensionality of gene expression data sets could go from several thousands to over 10,000 genes. A potential solution to this issue is using feature selection to reduce the dimensionality.

A computational model for emergent dynamics in the kidney.

In this paper, concepts from network automata are adapted and extended to model complex biological systems. Specifically, systems of nephrons, the operational units of the kidney, are modelled and the dynamics of such systems are explored. Nephron behaviour can fluctuate widely and, under certain conditions, become chaotic.