Information Technology Reference
In-Depth Information
Ta b l e 1 .
Different ways of modelling the foraging agent example
(a)
Q=
{
carrying nothing, has seen block, carrying block, at base
}
M = (Is carrying block, Is at base, Does see block), where Is carrying block,
Is at base, Does see block
∈{
true, false
}
m
o
= (false, false, false)
q
o
= carrying nothing
Σ
=
{
“move to a place w/o block”, “move to a place with block”, “pick block”,
“search for base”, “move to base”, “leave block”
}
Γ
=
{
“agent keeps moving empty”, “agent detected block”, “agent picked
block”, “agent searches for base”, “agent found base”, “agent left block”
}
(b)
Q=
{
carrying nothing, carrying block
}
M=((
X
,
Y
), (
X
base
,
Y
base
),
P
(
X
block
× Y
block
), Hand) where
X
,
Y
,
X
block
,
Y
block
,
X
base
,
Y
base
∈
Z
,Hand
∈{
full, empty
}
m
o
= ((2, 3) , (0, 0),
{
(2, -3), (4, -6), (2, 1), (3, 5), (-1, 5)
}
,empty)
q
o
= carrying nothing
Σ
=(
X
,
Y
), where
X
,
Y ∈
Z
Γ
=
{
“agent keeps moving empty”, “agent detected and picked block”, “agent
searches for base”, “agent found base and left block”
}
(c)
Q=
{
carrying nothing, carrying block
}
M=((
X
,
Y
), (
X
base
,
Y
base
), CarryingBlockId) where
X
,
Y
,
X
base
,
Y
base
∈
Z
, CarryingBlockId
∈{block
1
,
block
2
, ...
block
n
}∪
nil, n
∈
N
m
o
= ((2, 3), (0, 0), nil)
q
o
= carrying nothing
Σ
=((
X
,
Y
), BlockId), where
X
,
Y
∈
Z
,BlockId
∈{block
1
,
block
2
, ...
block
n
}∪{
nil
}
,n
∈
N
Γ
=
{
“agent keeps moving empty”, “agent detected and picked block”, “agent
searches for base”, “agent found base and left block”
}
2.2
Shortcomings of XM for Spatial Agents
The case study in the previous section demonstrated that there might be different ways
to modelling spatial agents with the XM approach, even for the simplest scenario. This
leads towards the identification of the following shortcomings when modelling spatial
agents with XM:
-
There might be many different solutions, even for the simplest model, for repre-
senting the commonly found properties, such as the initial position or the direction
of a spatial agent. This makes it more difficult to understand a given model (we
have to understand how the modeller decided to represent these properties), and
to create one (the modeller has to decide how to represent these properties on any
given case).
-
There are difficulties in simulating a given model because there is not a standard
way that deals with the manipulation and processing of the spatial properties like
the initial position or the direction of a spatial agent.
-
The memory holds all data structures required, including the position and the di-
rection.
