This research proposes an Activity Pattern embedded Air Pollution Exposure Model (AP2EM), based on survey data of when, where, and how people spend their time and indoor/outdoor ratios for microenvironments. AP2EM integrates random forest and agent-based approaches to simulate the stochastic...

Lithium (Li) metal is considered as one of the most exciting anode materials for next-generation batteries because of its high theoretical capacity and lowest reduction potential. However, the uncontrollable dendrite growth associated with nonuniform deposition and huge volume change during...

Countries all around the globe are continuing to restructure their energy markets in various ways. To deal with electricity market challenges, a flexible simulation platform is very important to maintain synchronization between market structure and market players and their behavior. So, for this...

Recently, multi-agent systems (MASs) have got attention due to consideration of distributed optimization and control in blockchain (BC) based energy trading applications. However, due to the dynamic behavior of uncertain and random variables, the coordination and control of MAS is still di cult...

We propose a behavioral heterogeneous agent New Keynesian model in which monetary policy is amplified through indirect general equilibrium effects, fiscal multipliers can be larger than one and which delivers empirically-realistic intertemporal marginal propensities to consume. Simultaneously,...

This study examines suppliers’ decision-making regarding supply chain ethics and transparency using an agent-based model with Q-learning agents. A supplier may not accurately identify the demand for its product because the impact of supply chain ethics on the market is opaque. Thus, we define...

Subscription decision in the telecom market is quite complex and cumbersome, invoking decision inertia in consumers and resulting in suboptimal choices. We implemented choice inertia and consumer interaction as an agent-based model to better understand the process. The model illustrates that...

Computing population moments for heterogeneous agent models is a necessary step for their estimation and evaluation. Computation based on Monte Carlo methods is usually time- and resource-consuming because it involves simulating a large sample of agents and potentially tracking them over time....