Autonomous AI systems need complex computational techniques for planning and performing actions. Planning and acting require significant deliberation because an intelligent system must coordinate and integrate these activities in order to act effectively in the real world. This book presents a comprehensive paradigm of planning and acting using the most recent and advanced automated-planning techniques. It explains the computational deliberation capabilities that allow an actor, whether physical or virtual, to reason about its actions, choose them, organize them purposefully, and act deliberately to achieve an objective. Useful for students, practitioners, and researchers, this book covers state-of-the-art planning techniques, acting techniques, and their integration which will allow readers to design intelligent systems that are able to act effectively in the real world.

The SHOP2 planning system received one of the awards for distinguished performance in the 2002 International Planning Competition. This paper describes the features of SHOP2 which enabled it to excel in the competition, especially those aspects of SHOP2 that deal with temporal and metric planning domains.

Background The COVID-19 pandemic is a global health crisis, yet certain countries have had far more success in limiting COVID-19 cases and deaths. We suggest that collective threats require a tremendous amount of coordination, and that strict adherence to social norms is a key mechanism that enables groups to do so. Here we examine how the strength of social norms—or cultural tightness–looseness—was associated with countries' success in limiting cases and deaths by October, 2020. We expected that tight cultures, which have strict norms and punishments for deviance, would have fewer cases and deaths per million as compared with loose cultures, which have weaker norms and are more permissive. Methods We estimated the relationship between cultural tightness–looseness and COVID-19 case and mortality rates as of Oct 16, 2020, using ordinary least squares regression. We fit a series of stepwise models to capture whether cultural tightness–looseness explained variation in case and death rates controlling for under-reporting, demographics, geopolitical factors, other cultural dimensions, and climate. Findings The results indicated that, compared with nations with high levels of cultural tightness, nations with high levels of cultural looseness are estimated to have had 4·99 times the number of cases (7132 per million vs 1428 per million, respectively) and 8·71 times the number of deaths (183 per million vs 21 per million, respectively), taking into account a number of controls. A formal evolutionary game theoretic model suggested that tight groups cooperate much faster under threat and have higher survival rates than loose groups. The results suggest that tightening social norms might confer an evolutionary advantage in times of collective threat. Interpretation Nations that are tight and abide by strict norms have had more success than those that are looser as of the October, 2020. New interventions are needed to help countries tighten social norms as they continue to battle COVID-19 and other collective threats. Funding Office of Naval Research, US Navy.

Automated composition of Web Services can be achieved by using AI planning techniques. Hierarchical Task Network (HTN) planning is especially well-suited for this task. In this paper, we describe how HTN planning system SHOP2 can be used with OWL-S Web Service descriptions. We provide a sound and complete algorithm to translate OWL-S service descriptions to a SHOP2 domain. We prove the correctness of the algorithm by showing the correspondence to the situation calculus semantics of OWL-S. We implemented a system that plans over sets of OWL-S descriptions using SHOP2 and then executes the resulting plans over the Web. The system is also capable of executing information-providing Web Services during the planning process. We discuss the challenges and difficulties of using planning in the information-rich and human-oriented context of Web Services.

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a b s t r a c tThe strengths of social norms vary considerably across cultures, yet little research has shown whether such differences have an evolutionary basis. Integrating research in cross-cultural psychology with evolutionary game theory, we show that groups that face a high degree of threat develop stronger norms for organizing social interaction, with a higher degree of norm-adherence and higher punishment for deviant behavior. Conversely, groups that have little threat can afford to have weaker norms with less punishment for deviance. Our results apply to two kinds of norms: norms of cooperation, in which individuals must choose whether to cooperate (thereby benefitting everyone) or enrich themselves at the expense of others; and norms of coordination, in which there are several equally good ways for individuals to coordinate their actions, but individuals need to agree on which way to coordinate. This is the first work to show that different degrees of norm strength are evolutionarily adaptive to societal threat. Evolutionary game theoretic models of cultural adaptation may prove fruitful for exploring the causes of many other cultural differences that may be adaptive to particular ecological and historical contexts.

Abstract. The DAML-S Process Model is designed to support the application of AI planning techniques to the automated composition of Web services. SHOP2 is an Hierarchical Task Network (HTN) planner well-suited for working with the Process Model. We have proven the correspondence between the semantics of SHOP2 and the situation calculus semantics of the Process Model. We have also implemented a system which soundly and completely plans over sets of DAML-S descriptions using a SHOP2 planner, and then executes the resulting plans over the Web. We discuss the challenges and difficulties of using SHOP2 in the information-rich and human-oriented context of Web services.

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