The phrase "agent behaviour" is correct and usable in written English.
It can be used in contexts related to psychology, artificial intelligence, or any field discussing the actions or responses of an agent, whether human or non-human.
Example: "The study focused on agent behaviour in virtual environments to understand how users interact with digital characters."
Alternatives: "agent actions" or "agent conduct".
In particular, modelling of the mobile agent behaviour is visual and its coding is seamlessly supported by the Mobile Active Object Framework.
The coded agent behaviour can be adapted to platform-specific mobile agents by means of the Mobile Agent Adaptation Framework thus enabling re-use of existing mobile agent systems.
Foxtons has argued that Budden had previously been paid at below the market rate, although the sales patter hasn't quite worked with an audience that seems to be sticking with the well-worn method of assessing estate agent behaviour: you can tell they are trying to shaft you when you see their lips move.
It also requires a stricter collaboration between game designers, domain experts and programmers than with scripting approaches, as agent behaviour is not solely defined by fixed scripts.
The editors developed this integrated book with three aims: to explain self-organisation concepts and principles, using clear definitions and a strong theoretical background; to examine how self-organising behaviour can be modelled, analysed and systematically engineered into agent behaviour; and to assess the types of problems that can be solved using self-organising multiagent systems.
The other approaches consider the whole system dynamics and link the concrete agent behaviour directly to their utility measure.
Refinements of agent behaviours such as these would clearly benefit from the collaboration of behavioural psychologists.
Norms have been promoted as a coordination mechanism for controlling agent behaviours in open MAS.
Practical agent languages and their corresponding architectures have often relied on a static plan library with more or less direct trigger-response activation mechanisms as a source for agent behaviours for the sake of runtime efficiency.
It allows users to simulate complex socio-environmental couplings in groundwater systems, and to explore how desirable patterns of groundwater and social development can emerge from agent behaviours and interactions.
The implementation and analysis of scenarios from this example highlight the possibility to: (i) deploy agents at multiple scales of decision-making (farmers, waterworks, institutions), (ii) model feedbacks between agent behaviours and groundwater dynamics, and (iii) perform sensitivity and multi-realisation analyses on social and physical factors.
