Computational Intelligence - November 2013 - 29
Deliberative Agent
process occurring within P; consequently a separate communiA deliberative agent is a tuple ag = {E, r, }, P, a} where the
cation channel exists between P and X to enable direct inforcomponents are as follows:
mation transfer between these engines without mediation from
E is a model of the environment, including the physical
A. All actions performed by R are passed through the Abstracdynamics of any agent present in the environment;
tion Engine for reification. In this way, R is a traditional BDI
1
r: P (W E) " P (L) is a function that converts raw sensor
agent dealing with discrete information, P and X are traditional
data into abstract statements in first order logic;
control systems, while A provides the vital "glue" between all
} 1 W E is a set describing the agent's current perceived
these parts by hosting primary communication channels and
context;
translating between continuous and abstract data. Interaction
P is a set of the executable plans of the agent; and
between the components in the architecture is governed by a lana: P (L) " P is a plan selector function that selects an individguage independent operational semantics [1].
ual plan p ! P using information from the abstractions of
The agent programming language within the Rational Engine
the sensor data created by r. a is, potentially, non-determinencourages an engineer to express decisions in terms of the facts
istic though it need not be.
available to an agent, what it wants to achieve and how it will cope
The agent, ag, evolves in environment E during successive
with any unusual events.This reduces code size so an engineer need
reasoning cycles that involve a selecting a new executable plan
not explicitly describe how the spacecraft should behave in each
from P based on which abstractions of } currently hold, or
possible configuration of the system, but can instead focus on those
leaving the currently chosen plan to continue execution. This is
facts that are relevant to particular decisions [39]. The key aspect of
a general definition that is not specific to the composition of }
deliberation within agent programs allows the decision making part
and P nor to individual implementations of r and a.
of the system to adapt intelligently to changing dynamic situations,
The structure and connection of modules in a software to
changing priorities, and unreliable hardware systems.The distinctive
implement the theoretical scheme in Figure 3 can look different.
features of our agent programming approach, which go beyond
Figure 2 illustrates the functional architecture of the agent that is
those of Jason or Gwendolen are as follows.
implemented within this article, which
comprises an augmented high-level reasoning system linked through an abstraction layer to low-level control and sensor
Environment
systems. Such real-time control and sensPropagate World
(Simulation or Real)
ing processes form a Physical Engine (P)
that is situated in an environment that
may be real or simulated; P consists of
the aspects that are able to sense and
Physical Engine (P)
Continuous Engine (X)
effect change in the environment. P
communicates with an Abstraction Engine
Sense/Act Loop(s)
Calculate
(A) . It is here that perception data is
sampled from P and subsequently filtered to prevent flooding of the belief
base that belongs to the Rational Engine
(R), which dictates processes occurring
Continuous Query
Continuous Action Continuous Sense
within P via A. R is the highest level
Abstraction
within the system and contains a "SenseLayer (A)
Abstract Action
Reason-Act" loop. Sensing here relates
Abstract Sense
Abstract Query
to the perception of changes within the
belief base that is being modified by A,
via filtered abstraction of data from P,
which may result in reasoning over new
Reasoning
events and result in actions necessitating
Engine (R)
Sense/Reason/Act
Loop(s)
interaction with either P or the ContinData Flow
uous Engine (X) . X augments R and is
Control Flow
utilized to perform complex numerical
procedures that may be used to assist reasoning processes within R or generate FIGURE 2 System structure: this maps onto the algorithmic description in Figure 1 by the
data that will be required for a physical "Abstraction layer" mapping onto the "Abstractor of higher level states", the "Physical Engine"
1
P ^ X h denotes the subsets of a set X .
maps to "Sensor/Perception Stream", the "Continuous Engine" to P and the "Environment" to E.
The reasoning engine block corresponds to the deliberative actions responsible for the appropriate selection of plans, and performs the role of a.
NOVEMBER 2013 | IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE
29
Table of Contents for the Digital Edition of Computational Intelligence - November 2013
Computational Intelligence - November 2013 - Cover1
Computational Intelligence - November 2013 - Cover2
Computational Intelligence - November 2013 - 1
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