SEKE 2012 Proceedings - Knowledge Systems Institute

current belief of agents in order to realize a new set of beliefs
for the system. The belief revision function allows a user to
refine and c ome up with a concrete set of beliefs to spe cify
intelligent software agents. The belief desire function is based
on the inputs passed on to the system and the a gent’s current
information on its en vironment. The following example
illustrates the belief revision function. The subnode that comes
along with the belief revision function is astate th at contains
the agents environment information.
agent(AIRCRAFT SOFTWARE_INPUTS)_AGENT
…
belief _desire _function
input
…
astate
…
The above example gives t he structure of a belief desire
function in a n agent system. Analysis and synt hesis trees
follow the decision construct to specify the intelligent agent
system completely and correctly.
3) Option generation function
An option generation function is used to generate options,
in other words, desires of the system based on environmental
state and set of intentions. Intentions are nothing but the set of
options that the syste m intends to achieve in the near future.
An option generation function is s pecified under the “ogf”
reserved word. This new exten sion to Descartes allows for
specifying the option generation function i n accordance with
the environmental states. Consider the following example:
ogf
list_of_options_for_the_agent_system
…
estate
‘S0’
‘S1’
‘S2’
intentions
‘I1’
‘I2’
‘I3’
The output from the “ogf” constr uct will be the set of options
in accordance with the beliefs and set of intentions.
4) Current options
Current options represent t he list of act ions that are
expected from an agent. Actions are the set of actions that an
agent can perform based on an a gents environmental state,
desires, and intentions. Th e reserved word “action” was
already added to the Descartes specification language to derive
a specific acti on that an int elligent software agent performs
under a certain circumstance. Based on the current
environment, the set of beliefs framed, and the set of
intentions, the corresponding action is taken . In th is way of
specification of an in telligent agent system, the environment
states which holds the information of agents from the past, is
used to re spond to the s urroundings in t he form of actions .
Action is represented through a serie s of a nalysis and
synthesis trees. Consider the following example:
action
ACTION_BASED_ON_ENVIR_STATE
IV.
AIRCRAFT SOFTWARE COMPONENT SPECIFICATION
The extensions made to the De scartes specification
language introduced in Section 4 ha ve been used to write
sample specifications for aircra ft software components. The
requirements described for Federal Aviation Regulation (FAR)
climb in a m ultiengine aircraft [5] has been converted into
specifications written using the extended Descartes
specification language. T he BDI a rchitecture for specifying
intelligent agent structures ha s been used to write
specifications for the ai rcraft design using the e xtended
Descartes constructs. An aircraft climb management system
follows to meet the Federal Aviation Regulations.
1) Sample specification 1
In sample specification 1, using extended Descartes
constructs, an aircraft climb management system is specified.
Operations are divided i nto two m ain categories na mely
takeoff climb, and landing. A Ho are tree structure that uses
analysis and s ynthesis trees, specifies the first se gment of
takeoff climb where the aircraft speed will be in Liftoff (LOF)
mode with gear down and flaps in the takeoff position. The
input and output to specifications 1 and 2 are described as
follows. Input to the two specifications are the values of the
current positions of the parameters of the aircraft management
system and the output of t he system will be the next position
the aircraft needs to take based on the intelligent agent
decisions.
agent (TURBINE_ENGINE_AIRCRAFT)_AGENT
TURBINE_ENGINE_AIRCRAFT
aircraft _sensors_input_signals *
in
put
speed +
FLOAT
LOF
flap +
takeoff
up
approach
landing
num
ber_engine
INTEGER
m
in_climb_gradient
FLOAT
landin g_gear +
up
down
estate
estate_name
‘V s0 ’
‘ V s1 ’
‘V s2 ’
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