We welcome regular papers, demo papers about benchmarks or tools, and position papers, and encourage discussions over a broad list of topics (not exhaustive):

• Analysis and comparisons of AI benchmarks and competitions. Lessons learnt.

• Proposals for new general tasks, evaluation environments, workbenches and general AI development platforms.

• Theoretical or experimental accounts of the space of tasks, abilities and their dependencies.

• Evaluation of development in robotics and other autonomous agents, and cumulative learning in general learning systems.

• Tasks and methods for evaluating: transfer learning, cognitive growth, structural self-modification and self-programming.

• Evaluation of social, verbal and other general abilities in multi-agent systems, video games and artificial social ecosystems.

• Evaluation of autonomous systems: cognitive architectures and multi-agent systems versus general components: machine learning techniques, SAT solvers, planners, etc.

• Unified theories for evaluating intelligence and other cognitive abilities, independently of the kind of subject (humans, animals or machines): universal psychometrics.

• Analysis of reward aggregation and utility functions, environment properties (Markov, ergodic, etc.) in the characterisation of reinforcement learning tasks.

• Methods supporting automatic generation of tasks and problems with systematically introduced variations.

• Better understanding of the characterisation of task requirements and difficulty (energy, time, trials needed..), beyond algorithmic complexity.

• Evaluation of AI systems using generalised cognitive tests for humans. Computer models taking IQ tests. Psychometric AI.

• Application of (algorithmic) information theory, game theory, theoretical cognition and theoretical evolution for the definition of metrics of cognitive abilities.

• Adaptation of evaluation tools from comparative psychology and psychometrics to AI: item response theory, adaptive testing, hierarchical factor analysis.

• Characterisation and evaluation of artificial personalities.

• Evaluation methods for multi-resolutional perception in AI systems and agents.