Workshop on Planning the Future: Economics and Value-Rational Decision Planning

Collocated with ICAPS 2019 in Berkeley, USA.

The 4th industrial revolution which is the confluence of the digital, physical and biological systems is changing the fields of engineering, finance and economics. One of the digital technologies that are changing this landscape is artificial intelligence (AI). In recent years, AI decision-making and autonomous systems have become an integrated part of the economy, industry and society. The evolving economy of the human-AI ecosystem raises concerns regarding value bias and risks inherited by AI systems. The availability and the increasing demand for AI systems created by many disciplines of intelligent systems addressing sub-aspects of the problem-solving process (e.g., different learning methods, data storage, information retrieval and more) create discrete components. These discrete components might individually be efficient and effective but as a combined system their effectiveness is reduced. Even though there is increasing efficiency of each intelligent system, this does not necessarily lead to increased effectiveness of the overall system. To explain this in optimization framework, each subsystem can individually optimize but collectively be sub-optimal. For example, face recognition systems can be individually optimized for sub-populations but not be globally optimized because they are based on partial data. Effective planning of a rational decision-making process is the natural tool that links and guides a divided process of practical problem-solving. Planning and problem-solving are decision-making processes that consist of sequential decision choices and decision actions.

Rational decision-making process comprises of rational decision actions and the entire process is optimized in time, space and overall utility resulting in a global optimum utility. However, global optimum utility is only attainable for convex problems and for non-convex problems one is never sure if the identified optimal utility is globally optimized. Decisions are the building blocks in most productive and intelligent activities. Thinking and problem solving are naturally multidisciplinary and require different cognitive skills at different stages and contexts. A well-planned problem-solving process allows combining multi-disciplinary decisions to a practical solution. On the one hand, the non-atomic nature of the decision-making process is vulnerable to communication and coordination limitations. On the other hand, this serves as a ground for multi-disciplinary collaboration and sharing of ideas, tools, real-world challenges and mutual feedback on each other’s work.

This workshop intends to build a bridge between many disciplines such as AI, optimization, planning, problem-solving and decision making. Furthermore, this workshop will bring together researchers and practitioners from academic, industry and economic environments. It is an opportunity to build a platform for ongoing cross-fertilization of ideas and tools to solve problems in planning. We accept papers, posters and demonstrations.

Topics of interests include but are not limited to:

This workshop will cover the philosophy, theory of value, rationality, causality, information ethics, value as well as knowledge bias and alignment in decision-making systems. The broad topics covered but not limited are as follows: The workshop will include invited talks, presentations of accepted papers (short and long), posters and demonstrations as well as a multi-disciplinary panel on the challenges and gaps in real-world planning, problem-solving, communication channels and ongoing collaboration between different disciplines. A summary panel will discuss action-items and priorities for future research to sketch a collaborative plan/policy for future research. Accepted papers will be published in the conference proceeding and selected papers will be published by CRC Press as an edited book.

Invited talks: * contact us to suggest or apply for invited talks. Submit your work here: (https://easychair.org/conferences/?conf=vrdip2019).

Submissions may be regular papers (up to 8 pages plus references), short position/challenge papers (up to 4 pages plus references), posters, applications, demonstrations materials, infographic

Submissions may (but not required) use the AAAI formatting guidelines and style (http://www.aaai.org/Publications/Author/author.php) and submitted via EasyChair web site.

Questions, Suggestions, Assistance and Answers

Submissions with different format or requirements, question, any issue/assistance in going through the submission process may be referred by email to: * We welcome existing publications from other venues that are appropriate for discussion at this workshop. Please note in the title area if this work is already accepted at another venue. If the work is under review at another venue (e.g. IJCAI) please notify the organizers so we can avoid potential reviewing conflicts.

To Ask For or/and To Suggest Collaboration, Feel Free To Contact Us Directly or at info@valuerationalplanning.com

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