Summary of the course Multi-agent systems (XB_0024) at the VU.
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Course
Multi-Agent Systems (XB_0024)
Institution
Vrije Universiteit Amsterdam (VU)
The Multi-Agent Systems course is given in the second year of the bachelor AI, at the Vrije Universiteit Amsterdam. This summary covers all lecture video's used in the year (during the COVID breakout). Mainly, the subjects on Prolog and GOAL will be covered.
Week 1, college 1
This course:
● Knowledge representation and agents & robotics
Intelligent agent paradigm
● An agent is anything that can be viewed as perceiving its environment through
sensors and acting upon that environment through effectors.
●
○ Processing is in ?
● Internally, an agent is agent = architecture + program
● Core business of AI: designing architectures and programs.
Natural agents
● Animals are agents
○ Can perceive their environment using their eyes, ears, skin, tongue and nose.
○ Can act upon their environments by their muscle motor systems, mounts
(sound)
○ Cognitive skills: perception, attention, memory, language, learning and
problem solving.
● Human agents
○ Can perceive their environment using their eyes, skin, tongue, nose.
○ Can act upon their environment by their muscle motor systems, mouth
(speech)
○ Are very versatile (ability to adapt): can survive in almost any environment on
earth.
○ Advanced cognitive skills: perception, attention, memory, language, learning,
and problem solving.
● Plants are agents too
○ Can perceive their environment using their sensors.
○ Can act upon their environment by their several muscles and systems.
● Agents are everywhere
○ an agent is anything that can be viewed as perceiving its environment through
sensors and acting upon that environment through effectors.
○ We are interested here in automated agents.
○ Websites also respond to their own environments.
● Robotic agents
○ Can perceive their environment using their cameras, microphones, touch
sensors,...
○ Can act upon their environment by their motor and sound systems, displays.
○ Are currently not very versatile:
■ Can function is specific contexts.
, ○ Do currently not yet have advanced cognitive skills:
■ Limited perception, attention, memory etc.
Intelligent agents
● Reactive:
○ Ability to receive information and respond.
● Proactive:
○ Ability to take the initiative.
● Social: ability to communicate and cooperate.
● Autonomous:
○ Agents control their own processes.
About being social
● Human interaction skills go way beyond the robot interactions skills yet.
○ But robots have their own repertoire for interaction, for example displays and
lights.
○ Robots do not try to replicate humans necessary.
Which are intelligent agents
● Plants are not really intelligent in intuition.
● It is not really clear what is intelligent and what not.
Cognitive(-affective) agents
● An agents is anything that can be (usefully) viewed as a system that has:
○ Beliefs, desires, goals, intentions, plans, expectations, hopes, fears, joy,...
○ …
Intentional systems
● First-order
○ bel(p): the agent believes that p
○ goal(p): the agent has a goal (or wants) that p
● Second-order
○ bel(a;bel(b;p)): a believes that p
○ We now use more first-order
Our notion of cognitive agent
● Agents with the following basic capabilities:
, ○ Event processing
■ Process events like percepts and messages.
○ Knowledge representation
■ Process events like percepts and messages.
■ It allows us to maintain a model of the environment and other agents.
○ Decision-making:
■ Agent is able to select an action based on its beliefs, knowledge, and
goals.
Cognitive state
● The internal state of a cognitive agent is called a cognitive state.
● Typically it includes
○ Event component
■ Percepts
■ Messages
○ Informational component:
■ Knowledge (static)
■ Beliefs (dynamic)
○ Motivational component (what the agent wants to achieve):
■ Goals
○
Environments
● It is very important to emphasize that agents are situated in an environment.
● Percepts:
○ Agents to usually not see the real state of the environment but only receive
percepts.
○ Designer:
■ The designer has to process percepts and possibly store them within
the agent’s memory.
○ Environment-properties:
■ As such it is very important to know the characteristics of an
environment, before designing an agent.
Properties of environments
● Fully/partially observable: if the environment is not completely observable the agent
will need internal states.
● Deterministic/stocastic:
○ Deterministic if completely determined by agent’s action.
, ○ If the environment is only partially observable, then it may appear stochastic
(while it is deterministic).
● Static/dynamic:
○ The environment can change while an agent is deliberating.
● Discrete/continuous: if there is a limited number of percepts and actions the
environment is discrete.
● Single/multi agents: is there just one agent or are there several interacting with each
other.
Cognitive agents and environments
● For cognitive agens we take the view the an en enviroment offers controllable entities
which are connected to cognitive agents.
● Possible view:
○ Cognitive agent is the mind
● controllable entity is the body.
●
● An action specification defines which actions are available to an agent and when.
○ It is defined by the environment.
Interaction with environment and agents
● Observation: how can the agent observe its environment?
○ Passive
■ The agent receives the results of observations without taking any
initiative or control to observe.
○ Active
■ The agent actively ini….
Summary
● The (material) world state
● Performing observations in the world
● Execution of action in the world
● Performing communication with other agents
● An agent’s own knowledge
● An agent’s own assumptions (for example beliefs)
● An agent’s own reasoning and acting processes.
● Other agent’s…
Cognitive agent programming
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