Agent Based Models ( Abm )

Models provide the physical testing and proof of a hypothesis by exploring the extent to which the two factors relate within the given hypothesis. It puts a theory into action, to see if the theory is corrected causes and effects.

Models provide the physical testing and proof of a hypothesis by exploring the extent to which the two factors relate within the given hypothesis. It puts a theory into action, to see if the theory is correct.

There are both different advantages and various of disadvantages of using models to produce knowledge in Natural Science and Human Science. According to Theory of Knowledge, “model is a simplified representation of some aspect of the world.” (IBO) It can be a simplified diagram of how a specific system or experiment works, or a long mathematical complicated equation. Those simplified representations further the knowledge in different ways such as understanding and prediction. From the heading, we can see that we have to examine the advantages and limitations of using models to produce knowledge in different areas of knowledge. Hence, in this essay, I will assess the advantages and limitations of using models in the role that they play in producing

A choice issues from, and can be sufficiently explained by, an agent’s character and motives, then to be ultimately responsible for the choice, the agent must be at least in part responsible by virtue of choices or actions voluntarily performed in the past for having the character and motives he now has (295).

Decreasing the complexity of modeling systems conceptually- this model stems from Hopper & Steve by using the conceptual models it gives leaders the ability to look at the different part of the system in order to view the current system in a different way to decrease the level of complexity.

Autocratic  Model: The basis of this model is power with a managerial orientation of authority. The employees in turn are oriented towards obedience and dependence on the boss. The employee need that is met is subsistence. The performance result is minimal.

A model is a representation of reality, designed to generate outputs from inputs in an attempt to understand system behaviour (Jones and Gomez, 2010). Many geographers refer to a model by the classic definition from Kolars and Haggett, 1967: "a simplified version of reality, built in order to demonstrate certain of the properties of reality". Models are often known as analogies which is a ‘relationship of similarity between two things, a likeness in some function, effect, or circumstance’ (Andrews, 1987). Analogue models are only one distinguished in physical geography. Conceptual, physical and mathematical models are also used (Jones and Gomez, 2010).

|Models may draw on a number of theories to help understand a particular problem in a |

An agent is in the privileged position to declare one’s intentions. The description of one’s actions and one’s intentions are the same. Anscombe starts off her notes by describing three different ways in which we speak about intention in our language:

Agents can be described as an individual’s or a group of people’s ability to exercise free will and the capability to make independent decisions. The decision made can led to social change, however, according to Giddens, these changes are not without influence, since a human behavioural patterns are depend on the structure, which is around the agent. Thus, while several theorist take a stand either on the view that people behave without external influence, or that individuals are always subjected to the external forces, Giddens has a dualistic approach and states that humans can both be determined by the structure and act according to their free

On degree of Abstraction: Modelling can be done with various degrees of abstraction and is classified into four groups: iconic, analogue, mathematical and mental by Turban et al (2001).

Several models exist for describing agent systems for comparative [1] or standardization purposes [5, 6]. However, for discussing security issues it is sufficient to use a very simple one, consisting of only two main components: the agent and the agent platform. Here, an agent comprises the code and state information needed to carry out some computation. As mentioned earlier, the computation is typically a goal-directed task, performed autonomously by the agent on behalf of some individual, with the cooperation of other agents. An agent's code tends to be static or unchanging, while its state information may vary dynamically, reflecting the results of the actions taken by the agent. Mobility allows an agent to move or hop among agent

The five agent-based technologies are currently being used in some capacity within OppenheimerFunds, Inc. as we used software such as intelligent agent for housing all our clients account information from invested funds, transactions performed and clients personal account information. In addition data-mining agents are used to understand the total investment by fund and ownership percentages. Another intelligent agent that we use is for our web transactions, which are then feed into various system for banking transactions, fund information, and account balancing.

A mathematical model is an idealisation of a real problem. Mathematical models also allow predictions to be made in studies. These models are usually expressed in functions. Graphs are then plotted from these functions and will be analysed. The mathematical model that will be studied in this investigation is mainly the cubic function.

An agent-based model (ABM) is used here to examine what effect village attitudes toward forest conservation have on the future landscape and extent of forest cover in Bachauli, Nepal if improved forest conservation-related policies are implemented, population growth rate fluctuates, and villages are able to mimic one another’s attitudes toward forest conservation-related behaviors and land use/land cover change (LULCC) decisions. The model integrates land cover data and household attitudes toward forest conservation, community forestry, and forest governance institutions in Nepal. Results suggest that implementing policies aimed at improving individual attitudes toward forest conservation-oriented behaviors would affect forest cover over time. The ability for villages to mimic their neighbors, regardless of varying probabilities of occurrence, was found to have little effect on forest cover. Additionally, population growth rate was found to have a significant effect on LULCC. Despite clear strengths, many challenges still exist with modeling forest conservation dynamics and LULCC in developing countries such as Nepal. Here, we give an overview of some of the challenges we encountered with modeling LULCC in the place-specific context of Bachauli, Nepal—highlighting specific areas in the field which necessitate future improvement.