Modeling Location Choice of Secondary Activities with a Social Network of Cooperative Agents

Activity-based models in transportation science focus on the description of human trips and activities. Modeling the spatial decision for so-called secondary activities is addressed in this paper. Given both home and work locations, where do individuals perform activities such as shopping and leisure? Simulation of these decisions using random utility models requires a full enumeration of possible outcomes. For large data sets, it becomes computationally unfeasible because of the combinatorial complexity. To overcome that limitation, a model is proposed in which agents have limited, accurate information about a small subset of the overall spatial environment. Agents are interconnected by a social network through which they can exchange information. This approach has several advantages compared with the explicit simulation of a standard random utility model: (a) it computes plausible choice sets in reasonable computing times, (b) it can be extended easily to integrate further empirical evidence about travel behavior, and (c) it provides a useful framework to study the propagation of any newly available information. This paper emphasizes the computational efficiency of the approach for real-world examples

Modeling and Analysis of Scholar Mobility on Scientific Landscape

Scientific literature till date can be thought of as a partially revealed landscape, where scholars continue to unveil hidden knowledge by exploring novel research topics. How do scholars explore the scientific landscape , i.e., choose research topics to work on? We propose an agent-based model of topic mobility behavior where scholars migrate across research topics on the space of science following different strategies, seeking different utilities. We use this model to study whether strategies widely used in current scientific community can provide a balance between individual scientific success and the efficiency and diversity of the whole academic society. Through extensive simulations, we provide insights into the roles of different strategies, such as choosing topics according to research potential or the popularity. Our model provides a conceptual framework and a computational approach to analyze scholars' behavior and its impact on scientific production. We also discuss how such an agent-based modeling approach can be integrated with big real-world scholarly data.Comment: To appear in BigScholar, WWW 201

An agent-based model of jaguar movement through conservation corridors

Wildlife corridors mitigate against habitat fragmentation by connecting otherwise isolated regions, bringing well established benefits to conservation both in principle and practice. Populations of large mammals in particular may depend on habitat connectivity, yet conservation managers struggle to optimise corridor designs with the rudimentary information generally available on movement behaviours. We present an agent-based model of jaguars (Panthera onca), scaled for fragmented habitat in Belize where proposals already exist for creating a jaguar corridor. We use a leastcost approach to simulate movement paths through alternative possible landscapes. Six different types of corridor and three control conditions differ substantially in their effectiveness at mixing agents across the environment despite relatively little difference in individual welfare. Our best estimates of jaguar movement behaviours suggest that a set of five narrow corridors may out-perform one wide corridor of the same overall area. We discuss the utility of ALife modelling for conservation management

Cognitively-inspired Agent-based Service Composition for Mobile & Pervasive Computing

Automatic service composition in mobile and pervasive computing faces many challenges due to the complex and highly dynamic nature of the environment. Common approaches consider service composition as a decision problem whose solution is usually addressed from optimization perspectives which are not feasible in practice due to the intractability of the problem, limited computational resources of smart devices, service host's mobility, and time constraints to tailor composition plans. Thus, our main contribution is the development of a cognitively-inspired agent-based service composition model focused on bounded rationality rather than optimality, which allows the system to compensate for limited resources by selectively filtering out continuous streams of data. Our approach exhibits features such as distributedness, modularity, emergent global functionality, and robustness, which endow it with capabilities to perform decentralized service composition by orchestrating manifold service providers and conflicting goals from multiple users. The evaluation of our approach shows promising results when compared against state-of-the-art service composition models.Comment: This paper will appear on AIMS'19 (International Conference on Artificial Intelligence and Mobile Services) on June 2

Agent based modeling and simulation of a pastoral-nomadic land use system

Almost half of Africa is covered by arid savannas, which are used as rangelands and are the source of livelihood for a vast population. To sustain pasture quality, degradation has to be avoided and efficient and sustainable land use strategies are needed. This paper describes the development of a simulation model representing the range management strategies of the Himba people in north-western Namibia. The model recognizes spatial factors and the impact of management decisions on ecosystem dynamics. The paper also describes the process of creating and validating a software application, and implementing the model

Agent based modeling and simulation of a pastoral-nomadic land use system

Almost half of Africa is covered by arid savannas, which are used as rangelands and are the source of livelihood for a vast population. To sustain pasture quality, degradation has to be avoided and efficient and sustainable land use strategies are needed. This paper describes the development of a simulation model representing the range management strategies of the Himba people in north-western Namibia. The model recognizes spatial factors and the impact of management decisions on ecosystem dynamics. The paper also describes the process of creating and validating a software application, and implementing the model

Emotional persistence in online chatting communities

How do users behave in online chatrooms, where they instantaneously read and write posts? We analyzed about 2.5 million posts covering various topics in Internet relay channels, and found that user activity patterns follow known power-law and stretched exponential distributions, indicating that online chat activity is not different from other forms of communication. Analysing the emotional expressions (positive, negative, neutral) of users, we revealed a remarkable persistence both for individual users and channels. I.e. despite their anonymity, users tend to follow social norms in repeated interactions in online chats, which results in a specific emotional "tone" of the channels. We provide an agent-based model of emotional interaction, which recovers qualitatively both the activity patterns in chatrooms and the emotional persistence of users and channels. While our assumptions about agent's emotional expressions are rooted in psychology, the model allows to test different hypothesis regarding their emotional impact in online communication.Comment: 34 pages, 4 main and 12 supplementary figure