New battery materials are constantly being invented, but there are still challenges in producing them at a large scale and at high quality. Through the power of artificial intelligence (AI) and advanced simulation, scientists can dramatically accelerate translating these materials from benchtop to large-scale manufacturing and in the process provide a way to generate higher-performance materials at scale. Argonne researchers are currently using AI to optimize nanomaterials produced from flame-spray pyrolysis (FSP) in a minimum number of trials. Argonne scientists are simultaneously building a comprehensive simulation of FSP to reveal the physics and inform the AI model. An advanced suite of diagnostics available at the FSP facility will provide validation data for the simulations.

Simulation is important for artificial intelligence because it provides solutions to some of the main problems faced by AI developers today. These solutions have immediate potential and are producing results already. Simulation is specifically useful for AI development in three key areas: training data, examining AI behavior, and providing learning environments. AnyLogic's white paper Artificial Intelligence and Simulation in Business explores the three areas and demonstrates, with examples, how general-purpose simulation and artificial intelligence work together. A business case shows how AnyLogic simulation and machine learning are already in use.

The Society for the Study of Artificial Intelligence and Simulation of Behaviour (AISB) is the largest Artificial Intelligence Society in the United Kingdom. Founded in 1964, the society has an international membership drawn from both academia and industry. It is a member of the European Coordinating Committee for Artificial Intelligence (see ECCAI benefits). AISB is a thriving learned society which invites membership from people with a serious interest in Artificial Intelligence, Cognitive Science and related areas. There are six types of membership: student, ordinary, benefactor, patron, corporate and institutional. Members of the Society receive a quarterly newsletter AISBQ which includes short reports on current AI and Cognitive Science research.

We have constructed this page in order to sketch how AI is linked to various other disciplines, in both the sciences and humanities. We have done this not only in the hope of helping students and others who are just starting to study AI but also of facilitating further interactions between the AI community and other communities. The set of links is not exhaustive, nor is the explanation given for each individual link. In particular, we do not include all disciplines that do or could use AI tools and/or contribute tools to AI. We concentrate rather on disciplines where there is profound interaction in terms of research ideas.

The difference between comedians and their audience is a matter not of kind, but of degree, a difference that is reflected in the vocational emphasis they place on humor. Researchers in the field of computational creativity find themselves in a similar situation. As a subdiscipline of artificial intelligence, computational creativity explores theories and practices that give rise to a phenomenon, creativity, that all intelligent systems, human or machine, can legitimately lay claim to. Who is to say that a given AI system is not creative, insofar as it solves nontrivial problems or generates useful outputs that are not hard wired into its programming? As with comedians' being funny, the difference between studying computational creativity and studying artificial intelligence is one of emphasis rather than one of kind: the field of computational creativity, as typified by a long-running series of workshops at AIrelated conferences, places a vocational emphasis on creativity and attempts to draw together the commonalities of what