Introduction
An Agent is anything that can be viewed as perceiving its environment through sensors and acting
upon that environment through effectors. Internally, an agent is: agent = architecture + program.
Core business of AI: designing agent architectures and programs.
Animals are agents: Can perceive their environment using their eyes, ears, skin (touch), tongue
(taste), nose (smell). Can act upon their environment by their muscle motor systems (moving),
mouth (sounds). Cognitive skills: perception, attention, memory, language, learning and problem
solving.
Human are agents. Can perceive their environment using their eyes, ears, skin, tongue, nose. Can act
upon their environment by their muscle motor systems (moving), 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… Can act upon their environment
by their…. Cognitive skills are not required.
An agent is anything that can be viewed as perceiving its environment through sensors and acting
upon that environment through sensors. But we are interest here in automated agents.
Robotic Agents can perceive their environment using their cameras, microphones, touch sensors,…
Can act upon the environment by their motor and sound systems, displays… Are currently not yet
very versatile: can function in specific contexts. Do currently not yet have advanced cognitive skills:
limited perception, attention, memory language, learning, and problem solving skills. But we can
program agents.
Intelligent agent:
- Reactive: ability to receive information and respond.
- Pro-active: ability to take the initiative
- Social: ability to communicate and cooperate
- Autonomous: agents control their own processes
HRI = AI + memory and attention
Cognitive(-affective) agents
A cognitive(-affective) agent is anything can be (usefully viewed) as a system that has:
- Beliefs, desires, goals, intentions, plans, expectations, hopes, fears, joy…
,Compare to: an agent is anything that can be viewed as perceiving its environment through sensors
and acting upon that environment through effectors or human agents have cognitive skills:
perception, attention, memory, language, learning and problem solving
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 b believes that p
- bel(a; goal(b; p)): a believes that b wants p
- goal(a; bel(b; p)): a wants that b believes that p
- goal (a; goal(b; p)): a wants that b wants p
Key notion of cognitive agent: agent with the following basic capabilities:
- Event processing: process events like percepts and messages
- Knowledge representation: process events like percepts and messages. It allows to maintain
a model of the environment and other agents. (e.g.: use propositional or FOL or Prolog)
- Decision-Making: agent is able to select an action based on its beliefs, knowledge and goals
Note: We are not concerned how to transform observations into symbolic representations. We
abstract this.
The internal state of a cognitive agent is called a cognitive state. Typically it includes:
- Event component
o Percepts
o Messages
- Informational component
o Knowledge (static)
o Beliefs (dynamic)
- Motivational component (what the agents wants to achieve)
o Goals
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 environment
- Fully/partially observable (can see everything/not everything: if the environment is not
completely observable the agent will need internal states.
- Deterministic/stochastic: 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 cannot change while an agent is deliberating. Static: 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 1 agent or are there several interacting with each other.
For cognitive agents we take the view the an environment offers controllable entities which are
connected to cognitive agents. Possible view: cognitive agent is the mind and controllable entity is
the body. And action specification defines which actions are available to an agent and when. It is
defined by the environment.
Observation how can the agent observe its environment?
- Passive: the agent receives the results of observations without taking an initiative or control
the observe
- Active: the agent actively initiates and controls which observations it wants to perform
Execution of actions: the agent is capable of making changes to the state of its environment by
initiating and executing actions,
Communication with other agents: 2 directions of communication are distinguished, which can
occur together:
- Outgoing: is the agent capable of communicating to another agent?
- Incoming: is the agent capable of receiving communication from another agent?
Summary: Agents need to reason about
- The (material) world state
- Performing observations in the world
An Agent is anything that can be viewed as perceiving its environment through sensors and acting
upon that environment through effectors. Internally, an agent is: agent = architecture + program.
Core business of AI: designing agent architectures and programs.
Animals are agents: Can perceive their environment using their eyes, ears, skin (touch), tongue
(taste), nose (smell). Can act upon their environment by their muscle motor systems (moving),
mouth (sounds). Cognitive skills: perception, attention, memory, language, learning and problem
solving.
Human are agents. Can perceive their environment using their eyes, ears, skin, tongue, nose. Can act
upon their environment by their muscle motor systems (moving), 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… Can act upon their environment
by their…. Cognitive skills are not required.
An agent is anything that can be viewed as perceiving its environment through sensors and acting
upon that environment through sensors. But we are interest here in automated agents.
Robotic Agents can perceive their environment using their cameras, microphones, touch sensors,…
Can act upon the environment by their motor and sound systems, displays… Are currently not yet
very versatile: can function in specific contexts. Do currently not yet have advanced cognitive skills:
limited perception, attention, memory language, learning, and problem solving skills. But we can
program agents.
Intelligent agent:
- Reactive: ability to receive information and respond.
- Pro-active: ability to take the initiative
- Social: ability to communicate and cooperate
- Autonomous: agents control their own processes
HRI = AI + memory and attention
Cognitive(-affective) agents
A cognitive(-affective) agent is anything can be (usefully viewed) as a system that has:
- Beliefs, desires, goals, intentions, plans, expectations, hopes, fears, joy…
,Compare to: an agent is anything that can be viewed as perceiving its environment through sensors
and acting upon that environment through effectors or human agents have cognitive skills:
perception, attention, memory, language, learning and problem solving
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 b believes that p
- bel(a; goal(b; p)): a believes that b wants p
- goal(a; bel(b; p)): a wants that b believes that p
- goal (a; goal(b; p)): a wants that b wants p
Key notion of cognitive agent: agent with the following basic capabilities:
- Event processing: process events like percepts and messages
- Knowledge representation: process events like percepts and messages. It allows to maintain
a model of the environment and other agents. (e.g.: use propositional or FOL or Prolog)
- Decision-Making: agent is able to select an action based on its beliefs, knowledge and goals
Note: We are not concerned how to transform observations into symbolic representations. We
abstract this.
The internal state of a cognitive agent is called a cognitive state. Typically it includes:
- Event component
o Percepts
o Messages
- Informational component
o Knowledge (static)
o Beliefs (dynamic)
- Motivational component (what the agents wants to achieve)
o Goals
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 environment
- Fully/partially observable (can see everything/not everything: if the environment is not
completely observable the agent will need internal states.
- Deterministic/stochastic: 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 cannot change while an agent is deliberating. Static: 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 1 agent or are there several interacting with each other.
For cognitive agents we take the view the an environment offers controllable entities which are
connected to cognitive agents. Possible view: cognitive agent is the mind and controllable entity is
the body. And action specification defines which actions are available to an agent and when. It is
defined by the environment.
Observation how can the agent observe its environment?
- Passive: the agent receives the results of observations without taking an initiative or control
the observe
- Active: the agent actively initiates and controls which observations it wants to perform
Execution of actions: the agent is capable of making changes to the state of its environment by
initiating and executing actions,
Communication with other agents: 2 directions of communication are distinguished, which can
occur together:
- Outgoing: is the agent capable of communicating to another agent?
- Incoming: is the agent capable of receiving communication from another agent?
Summary: Agents need to reason about
- The (material) world state
- Performing observations in the world
