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Multi-agent systems (MAS) have recently evolved as an important feature in the development of future smart grids, especially to provide the fast-responding self-healing ability to the grid. This paper presents a comparative analysis of centralized and decentralized MAS architecture for the problem of service restoration. Service restoration is formulated as a multi-objective optimization problem and...
This paper presents a novel power flow optimization strategy in Micro Grids (MGs) connected to the main grid. When the MG includes stochastic energy sources, such as photovoltaic and micro eolic-generators, it is very useful to rely on Energy Storage Systems (ESSs) to buffer energy. In fact, an ESS can be employed to perform several functionalities, related to different user requirements, such as...
A polyomino puzzle is a collection of polyominos that can be joined to make a simple shape. The game Ten-Yen was one of the first of these. It has ten polyomino pieces that could be used to make a 6×6 square in a variety of ways. In this study we define representations and fitness functions for generating polyomino puzzles as well as developing a simple solver to compare the evolved puzzles. The solver...
Evolution of cooperation has been actively studied in the evolutionary computation (EC) community mainly for the iterated prisoner's dilemma (IPD) game. One of the frequently examined settings is a noisy environment where a player chooses a different action from the suggested one by its strategy with a pre-specified error probability. The use of the error probability in the IPD game usually makes...
Divide the dollar is a two-player simultaneous derived from a game invented by John Nash because its strategy space has an entire subspace of Nash equilibria. This study describes and explores a family of generalizations of divide the dollar with easily controlled properties. If we view divide the dollar as modeling the process of making a bargain, then the generalized game makes it easy to model...
Spatial games are extensively used to study how cooperation evolves in human populations. Nevertheless, spatial games have several limitations which can produce misleading results. Specifically, the regular lattice structure creates artificial interactions and the reliance on a Moran process updating, coupled with weak selection, makes it difficult to switch strategies. These problems contribute to...
Many variations of Monte Carlo tree search have been proposed and tested but relatively little comparison of these variants have occurred. In this study an Agent Case Embedding analysis and agglomorative hierarchical clustering was performed using eight variants of Monte Carlo Tree Search as agents and eight games as cases. This allowed us to compare the variant's abilities on each of the games to...
The iterated prisoner's dilemma is a simultaneous two-player game widely used in studies on cooperation and conflict. Past work has shown that the choice of representation or available resources such as the number of states or neurons of evolving agents has a large impact on the behavior of evolved agents. This study revisits three qualities of the agent training algorithm for finite state agents...
Design of multi-component structures can be a challenging task. While having multiple components in a complex structure is often necessary in order to reduce the manufacturing cost, multiple components need joining operations. Optimal design of joints is not a decoupled problem from designing the base structure, and often comes at balancing trade-offs in assembly cost, weight and structural performance...
A key component of model-based testing is the generation of test data from constraints (e.g., specified in the Object Constraint Language (OCL)) associated with models e.g., specified in the Unified Modeling Language (UML). The quality of test data eventually determines the effectiveness of test cases, e.g., fault detection and coverage. A simple way to generate test data from an OCL constraint is...
Friction Stir Welding (FSW) is an innovative manufacturing process, which is used to join two pieces of metal with frictional heating and plastic deformation due to stirring action. Melting is avoided during the process, therefore problems related to microstructure phase transformation (i.e., cooling from the liquid phase) are avoided. The temperature distribution in the weld zone, as a function of...
Urban planners face increasing challenges to design and optimize sustainable cities. Evolutionary algorithms are an important tool for design optimization and can help urban planners finding alternative optimal designs to increase the sustainability of cities. Mobility and transportation are two important components of modern cities that are amenable to simulation and their design can be improved...
Methods aiming detection and inference of spatial clusters are of great relevance. Both for its applicability to public health problems, as well as for the effective scientific interest in the development of these methods. The main techniques are based on spatial scan statistics and many applications link this statistic in efficient optimization methods. Recently, regularity functions have been proposed...
The idea of using the gait of a walking person as a biometric identification method has been seen in a number of proposed authentication methods, yet previous works focus on the addition of other authentication methods along with the gait, or require a stationary sensor attached to the hip of the user. This paper uses Genetic Programming to model an identification gait fingerprint for two users, whose...
Bare-bones Particle Swarm Optimization (BPSO) is a simplified PSO variant, which has shown potential performance on many multimodal optimization problems. However, BPSO is also possible to be trapped into local optima for high-dimensional and complicated optimization problems. In order to enhance the performance of BPSO, this paper presents a modified BPSO, called NMBPSO. It combined the ideas of...
Previous studies of feedforward neural networks (FFNNs) have found that asymptotically bounded activation functions used by particle swarm optimised (PSO) FFNNs have a significant impact on the swarm behaviour and FFNN performance. A number of alternative activation functions have however been developed that offer potential advantages over popularly used functions. The purpose of this study is to...
The performance of the Particle Swarm Optimization (PSO) algorithm can be greatly improved if the parameters are appropriately tuned. However, tuning the control parameters for PSO algorithms has traditionally been a time-consuming, empirical process. Furthermore, ideal parameters may be time-dependent. To address the issue of parameter tuning, self-adaptive PSO (SAPSO) algorithms adapt the PSO control...
This paper describes an extension to overlapping swarm intelligence for training artificial neural networks. Overlapping swarm intelligence is an application of particle swarm optimization that divides the network into paths from input to output, with each path represented by a swarm. Previous versions of this algorithm showed success on training networks on a variety of datasets but the method suffers...
At present, very little theoretical analysis has been performed on the unified particle swarm optimizer (UPSO). This paper derives the order-1 and order-2 stable regions for the UPSO algorithm, along with the fixed point of particle convergence. The impact that the unification factor has on the stability of UPSO is also analyzed. The theoretical analysis is performed under the stagnation assumption;...
Biogeography-based optimization (BBO) is a powerful evolutionary algorithm inspired from the science of biogeography. It mainly uses the biogeography-based migration operator to share the information among individuals. In canonical BBO, according to the principle of immigration and emigration, poor solutions are like to be completely replaced by better ones. Consequently, this will lead to reduction...
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