public class DynamicWeightedAStar extends AStar
If a terminal function is provided via the setter method defined for OO-MDPs, then the BestFirst search algorithm will not expand any nodes that are terminal states, as if there were no actions that could be executed from that state. Note that terminal states are not necessarily the same as goal states, since there could be a fail condition from which the agent cannot act, but that is not explicitly represented in the transition dynamics. 1. Pohl, Ira (August, 1973). "The avoidance of (relative) catastrophe, heuristic competence, genuine dynamic weighting and computational issues in heuristic problem solving". Proceedings of the Third International Joint Conference on Artificial Intelligence (IJCAI-73) 3. California, USA. pp. 11-17.
DeterministicPlanner.PlanningFailedException
Modifier and Type | Field and Description |
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protected java.util.Map<HashableState,java.lang.Integer> |
depthMap
Data structure for storing the depth of explored states
|
protected double |
epsilon
parameter > 1 indicating the maximum amount of greediness; the larger the more greedy.
|
protected int |
expectedDepth
The expected depth required for a plan
|
protected int |
lastComputedDepth
maintains the depth of the last explored node
|
cumulatedRewardMap, heuristic, lastComputedCumR
gc, internalPolicy
actions, debugCode, domain, gamma, hashingFactory, mapToStateIndex, rf, tf
Constructor and Description |
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DynamicWeightedAStar(Domain domain,
RewardFunction rf,
StateConditionTest gc,
HashableStateFactory hashingFactory,
Heuristic heuristic,
double epsilon,
int expectedDepth)
Initializes the valueFunction.
|
Modifier and Type | Method and Description |
---|---|
double |
computeF(PrioritizedSearchNode parentNode,
GroundedAction generatingAction,
HashableState successorState)
This method returns the f-score for a state given the parent search node, the generating action, the state that was produced.
|
protected double |
epsilonWeight(int depth)
Returns the weighted epsilon value at the given search depth
|
void |
insertIntoOpen(HashIndexedHeap<PrioritizedSearchNode> openQueue,
PrioritizedSearchNode psn)
This method is used to insert a prioritized search node into the openQueue.
|
SDPlannerPolicy |
planFromState(State initialState)
Plans and returns a
SDPlannerPolicy . |
void |
postPlanPrep()
This method is called at the end of the
BestFirst.planFromState(State) method and can be used clean up any special
data structures needed by the subclass. |
void |
prePlanPrep()
This method is called at the start of the
BestFirst.planFromState(State) method and can be used initialize any special
data structures needed by the subclass. |
void |
updateOpen(HashIndexedHeap<PrioritizedSearchNode> openQueue,
PrioritizedSearchNode openPSN,
PrioritizedSearchNode npsn)
This method is called whenever a search node already in the openQueue needs to have its information or priority updated to reflect a new search node.
|
deterministicPlannerInit, encodePlanIntoPolicy, hasCachedPlanForState, planContainsOption, planHasDupilicateStates, querySelectedActionForState, resetSolver
addNonDomainReferencedAction, getActions, getAllGroundedActions, getDebugCode, getDomain, getGamma, getHashingFactory, getRf, getRF, getTf, getTF, setActions, setDebugCode, setDomain, setGamma, setHashingFactory, setRf, setTf, solverInit, stateHash, toggleDebugPrinting, translateAction
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
addNonDomainReferencedAction, getActions, getDebugCode, getDomain, getGamma, getHashingFactory, getRf, getRF, getTf, getTF, setActions, setDebugCode, setDomain, setGamma, setHashingFactory, setRf, setTf, solverInit, toggleDebugPrinting
protected double epsilon
protected int expectedDepth
protected java.util.Map<HashableState,java.lang.Integer> depthMap
protected int lastComputedDepth
public DynamicWeightedAStar(Domain domain, RewardFunction rf, StateConditionTest gc, HashableStateFactory hashingFactory, Heuristic heuristic, double epsilon, int expectedDepth)
domain
- the domain in which to planrf
- the reward function that represents costs as negative rewardgc
- should evaluate to true for goal states; false otherwisehashingFactory
- the state hashing factory to useheuristic
- the planning heuristic. Should return non-positive values.epsilon
- parameter > 1 indicating greediness; the larger the value the more greedy.expectedDepth
- the expected depth of the planpublic void prePlanPrep()
BestFirst
BestFirst.planFromState(State)
method and can be used initialize any special
data structures needed by the subclass. By default it does nothing.prePlanPrep
in class AStar
public void postPlanPrep()
BestFirst
BestFirst.planFromState(State)
method and can be used clean up any special
data structures needed by the subclass. By default it does nothing.postPlanPrep
in class AStar
public void insertIntoOpen(HashIndexedHeap<PrioritizedSearchNode> openQueue, PrioritizedSearchNode psn)
BestFirst
PrioritizedSearchNode
with more information),
it can override it.insertIntoOpen
in class AStar
openQueue
- the open queue in which the search node will be inserted.psn
- the search node to insert.public void updateOpen(HashIndexedHeap<PrioritizedSearchNode> openQueue, PrioritizedSearchNode openPSN, PrioritizedSearchNode npsn)
BestFirst
PrioritizedSearchNode
with more information), it can override this method.updateOpen
in class AStar
openQueue
- the open queue in which the search node exists.openPSN
- the search node indexed in the open queue that will be updated.npsn
- the new search node that contains the updated information.public SDPlannerPolicy planFromState(State initialState)
SDPlannerPolicy
. If
a State
is not in the solution path of this planner, then
the SDPlannerPolicy
will throw
a runtime exception. If you want a policy that will dynamically replan for unknown states,
you should create your own DDPlannerPolicy
.
planFromState
in interface Planner
planFromState
in class BestFirst
initialState
- the initial state of the planning problemSDPlannerPolicy
.public double computeF(PrioritizedSearchNode parentNode, GroundedAction generatingAction, HashableState successorState)
BestFirst
computeF
in class AStar
parentNode
- the parent search node (and its priority) that from which the next state was generated.generatingAction
- the action that was used to generate the next state.successorState
- the next state that was generatedprotected double epsilonWeight(int depth)
depth
- the search depth