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It has been stated in psychology that human brain arranges
information in a way that improves efficiency in performing common
tasks, for example, information about our spatial environment is
conveniently structured for efficient route finding. On the other
hand, in computational sciences, the use of hierarchical
information is well known for reducing the complexity of solving
problems. This book studies hierarchical representations of
large-scale space and presents a new model, called Multi-AH-graph,
that uses multiple hierarchies of abstraction. It allows an agent
to represent structural information acquired from the environment
(elements such as objects, free space, etc., relations existing
between them, such as proximity, similarity, etc. and other types
of information, such as colors, shapes, etc). The Multi-AH-graph
model extends a single hierarchy representation to a mUltiple
hierarchy arrangement, which adapts better to a wider range of
tasks, agents, and environments. We also present a system called
CLAUDIA, which is an implementation of the task-driven paradigm for
automatic construction of multiple abstractions: a set of
hierarchies of abstraction will be "good" for an agent if it can
reduce the cost of planning and performing certain tasks of the
agent in the agent's world. CLAUDIA constructs multiple hierarchies
(Multi-AH-graphs) for a given triple , trying to optimize their
"goodness".
It has been stated in psychology that human brain arranges
information in a way that improves efficiency in performing common
tasks, for example, information about our spatial environment is
conveniently structured for efficient route finding. On the other
hand, in computational sciences, the use of hierarchical
information is well known for reducing the complexity of solving
problems. This book studies hierarchical representations of
large-scale space and presents a new model, called Multi-AH-graph,
that uses multiple hierarchies of abstraction. It allows an agent
to represent structural information acquired from the environment
(elements such as objects, free space, etc., relations existing
between them, such as proximity, similarity, etc. and other types
of information, such as colors, shapes, etc). The Multi-AH-graph
model extends a single hierarchy representation to a mUltiple
hierarchy arrangement, which adapts better to a wider range of
tasks, agents, and environments. We also present a system called
CLAUDIA, which is an implementation of the task-driven paradigm for
automatic construction of multiple abstractions: a set of
hierarchies of abstraction will be "good" for an agent if it can
reduce the cost of planning and performing certain tasks of the
agent in the agent's world. CLAUDIA constructs multiple hierarchies
(Multi-AH-graphs) for a given triple , trying to optimize their
"goodness".
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