00000ctm a22000004a 4500 UP-99796217603116329 Buklod 20230503092542.0 m |o d | ta 070717s2005 xx r |||| u|eng d (iLib)UPD-00000179772 DENGII eng LG 993.5 2005 C65 M36 Manansala, Kevin L. AMASSIS a multi-agent system simulation of the immune system Kevin L. Manansala, Pauline L. Rodriguez, Karen Desiree L. Tan. 2005. vii, 54 leaves col. ill. Thesis (B.S. Computer Science)--University of the Philippines, Diliman. AMASSIS, A Multi-Agent System Simulation of the Immune System, is a project geared towards the construction of a multi-agent based simulator of the Human Immune System, mimicking the actual operations and activities of its components. In this project, the Immune System is implemented as a Multi-Agent System composed of multiple cells in an environment. An agent is defined to be an entity that is in an environment, which has the capability of sensing its surroundings, and performs actions that can affect the state of that environment. The agent's decision on what to do is based on its objectives and what it can sense around it. The agents interacts with each other to achieve their specific goals that are based on the behavior of the different cells namely the B cell, Helper T cell, Killer T Cell, Antibody, Antigen Presenting Cell, and the Antigen. The agents in this project are basically software routines coded in such a way that they can represent the cells included in the simulation. The simulation could be used to observe the behavior of the Immune System under different conditions. There are two versions of the AMASSIS project. First is the AMASSIS Basic simulator, which simulates the humoral response of the immune system against a generic type of antigen. From this, a specialized simulator was developed. The AMASSIS Malaria simulator was designed to simulate the humoral and cellular responses of the immune system specifically against the infection of malaria antigen. Immune system Computer simulation. Neural networks (Computer science) AMASSIS (A Multi-Agent System Simulation of the Immune System). Rodriguez, Pauline L. Tan, Karen Desiree L. Thesis FI UP UPD DENG-II LG 993.5 2005 C65 M36 Thesis