Attributes Of Agents Research Articles

How artificial intelligence cooperating with agent‐based modeling for urban studies: A systematic review

AbstractAs urbanization accelerates, cities become more complex, coming along with more complex urban issues. Agent‐based model (ABM) is a traditional method to simulate activities in a complex system, which has been widely applied in urban studies. However, due to its rigid initial settings, ABM has been criticized for its lack of intelligence, especially in dealing with modern urban issues. With the success of artificial intelligence (AI) and complexity science, it is generally agreed that ABM can be enhanced with AI agents, a promising technology that can bridge the gaps. For that, this article provides a systematic review, in which 10 subsections correspond to 10 different ways that AI can work with ABM in the methodological framework. The sections include that (1) ABM is Al; (2) ABM provides training data for Al; (3) Al provides data for ABM; (4) ABM is a submodule in the ensemble Al; (5) Al leads an optimization framework with ABM participation; (6) Al tunes ABM initialization parameters; (7) Al provides the environment for ABM; (8) Al aids in choosing the agent's attributes; (9) Al provides behaviors for agents in ABM; (10) Al helps to evaluate the performance of ABM. For each case, some typical works are examined for illustration. Finally, we discuss some of the current limitations and prospects for future development.

Business Innovations and Interorganizational Relationships In the Hospitality Industry: Does Partner Diversity Matter?

Innovation is a potential source of differentiation and competitive advantage for the hospitality industry. However, the dynamism of the environment forces hotel operators to establish multiple and simultaneous interorganizational relations—portfolio of alliances—in order to provide the accommodation service and develop innovation activities while being efficient, aimed at remaining competitive in dynamic contexts. The benefits obtained, considering the set of relationships from a global perspective, are superior to those addressing alliances from an individual point of view. Bearing this in mind, this study empirically tests how the diversity among the agent's attributes—resources and cognitive schemes—within the portfolio of alliance can affect the introduction of business innovations. It is also analyzed whether the previous experience in collaboration of the hotel firm moderates this relationship. The results reveal that hotel companies must design their partner configuration according to the type of innovation to be introduced, focusing mainly on areas such as service and marketing.

An agent-based simulation model to evaluate the response to seismic retrofit promotion policies

Building owners’ appropriate risk-mitigation decisions can minimize the social, economic, and socioeconomic consequences of earthquakes. Implementation of appropriate policies can increase the adoption of seismic retrofit measures through the modification of owners’ beliefs. Social interactions among owners can influence their response to the implemented policies. There is a need for appropriate tools that consider the social interactions among the owners and facilitate the evaluation of their response to seismic retrofit promotion policies. The agent-based simulation model in this manuscript addresses this need. The implementation of policies and interactions among agents can influence agent's attributes. In this model, a set of behavior functions determine the impact of adjustments in owners’ attributes on their intentions and decisions. The relative agreement model used in the model characterizes the impact of agent interactions on their beliefs. The model outputs illustrate the gradual changes in the behavior of individual owners and their aggregate response to the implemented policy interventions. The capabilities of the proposed model are showcased by using an illustrative example. The example provides valuable insights on the diffusion of the impact of policies through society due to the agents’ interactions and shows that interactions among agents can enhance or nullify the impact of the implemented policies, based on the attitudes of the majority. Practitioners can use the proposed agent-based model to design new policies and select appropriate implementation mechanisms that effectively increase the adoption of risk-mitigation measures and enhance the resilience of communities.

Collective emotion dynamics in chats with agents, moderators and Bots

Using agent-directed simulations, we investigate fluctuations in the collective emotional states on a chat network where agents interchange messages with a fixed number of moderators and emotional Bot. To design a realistic chat system, the interaction rules and some statistical parameters, as well as the agent's attributes, are inferred from the empirical chat channel \texttt{Ubuntu}. In the simulations, the Bot's emotion is fixed; the moderators tune the level of its activity by passing a fraction $\epsilon$ of messages to the Bot. At $\epsilon \gtrsim 0$, the collective emotional state matching the Bot's emotion polarity gradually arises; the average growth rate of the dominant emotional charge serves as an order parameter. Due to self-organizing effects, the collective dynamics is more explosive when positive emotions arise by positive Bot than the onset of negative emotions in the presence of negative Bot at the same $\epsilon$. Furthermore, when the emotions matching the Bot's emotion polarity are spread over the system, the underlying fractal processes exhibit higher persistence and stronger clustering of events than the processes spreading of emotion polarity opposite to the Bot's emotion. On the other hand, the relaxation dynamics is controlled by the external noise; the related nonextensive parameter, estimated from the statistics of returns, is virtually independent of the Bot's activity level and emotion contents.

AGENT-BASED SIMULATION OF CONSUMER DEMAND FOR SMART METERING TARIFFS

An agent-based model simulates consumer demand for smart metering tariffs. It utilizes the Bass Diffusion Model and Rogers's adopter categories to locate demand-side barriers and drivers. Integration of empirical census microdata enables a validated socio-economic background for each consumer. The key performance indicators diffusion-speed and diffusion-level measure the effectiveness of regulatory interventions to induce diffusion. Pricing, promotion and quantity-regulation policies are tested. Scenario results emphasize the impact of both epidemic and probit effects. Speed of adoption is mainly triggered via interactions and consumer awareness. Level of diffusion primarily depends on pricing, willingness-to-pay and cost-benefit-thresholds. Data mining on agent's attributes highlight weaknesses in current regulatory requirements due to disadvantages in consumer acceptance and policy effectiveness. A "cash-for-clunkers" program could tackle major barriers for adoption and boost diffusion through synergies of pricing and promotion interventions.

Research on the attributes of rational agent’s internal states

Which attributes are the basic ones when we describe the rational agent's internal states? How many attributes are sufficient enough for application? Those have been pending problems. This paper analyzes the limitations of the past research in this field, presents rational agent's attributes of KOCBDI and illustrates, by means of simulated RoboCup, that KOCBDI is independent.