We will develop agent based modelling (ABM) for doing logic programming and Reverse Analysis method in doing higher order logic programming. Later, we will build another ABM for the upgraded method (integrating Boltzmann machine and Modify Activation Function). Agent-based Modelling (ABM) which also called individual-based modelling is a new computational modelling paradigm which is an analyzing systems that representing the 'agents' that involving and simulating of their interactions. We will test ABM for this upgraded method (higher order logic programming, Hopfield network, Boltzmann machine and activation function in some real life and simulated data sets. We are going to test this method on some constraint optimization problems
In recent years, the study of immune response behaviour using bottom up approach, Agent Based Modeli...
Agent-based modeling (ABM) is a well-established paradigm for simulating complex systems via interac...
Agent based models (ABM) have been recently applied to solve optimization problems whose domains pre...
Neural network and logic integration is the latest trend in Artificial Intelligence. Neural Symbolic...
This paper shows on developing agent based modelling for represent the performance of doing logic pr...
Logic program and neural networks are two important perspectives in artificial intelligence. The maj...
Logic program and neural networks are two important aspects in artificial intelligence. This paper i...
For higher-order programming, higher order network architecture is necessary as high order neural ne...
Agent-based modeling and simulation (ABMS) is a new approach to modeling systems comprised of intera...
tio on 60 Agent-based modeling and simulation (ABMS) is a new approach to modeling systems comprised...
This paper describes an agent-based method for modeling and simulation of the cerebellar cortex of n...
This document is the result of an exploratory project looking into the status of, and opportunities ...
The understanding of human central nervous system (CNS) depends on knowledge of its wiring. However,...
Artificial Neural Network (ANN) uses many activation functions to update the state on neuron. The re...
While agent-based modeling (ABM) has become one of the most powerful tools in quantitative social sc...
In recent years, the study of immune response behaviour using bottom up approach, Agent Based Modeli...
Agent-based modeling (ABM) is a well-established paradigm for simulating complex systems via interac...
Agent based models (ABM) have been recently applied to solve optimization problems whose domains pre...
Neural network and logic integration is the latest trend in Artificial Intelligence. Neural Symbolic...
This paper shows on developing agent based modelling for represent the performance of doing logic pr...
Logic program and neural networks are two important perspectives in artificial intelligence. The maj...
Logic program and neural networks are two important aspects in artificial intelligence. This paper i...
For higher-order programming, higher order network architecture is necessary as high order neural ne...
Agent-based modeling and simulation (ABMS) is a new approach to modeling systems comprised of intera...
tio on 60 Agent-based modeling and simulation (ABMS) is a new approach to modeling systems comprised...
This paper describes an agent-based method for modeling and simulation of the cerebellar cortex of n...
This document is the result of an exploratory project looking into the status of, and opportunities ...
The understanding of human central nervous system (CNS) depends on knowledge of its wiring. However,...
Artificial Neural Network (ANN) uses many activation functions to update the state on neuron. The re...
While agent-based modeling (ABM) has become one of the most powerful tools in quantitative social sc...
In recent years, the study of immune response behaviour using bottom up approach, Agent Based Modeli...
Agent-based modeling (ABM) is a well-established paradigm for simulating complex systems via interac...
Agent based models (ABM) have been recently applied to solve optimization problems whose domains pre...