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java.lang.Objectclarion.system.TaskClarion
Field Summary | |
static int |
ACS
constants for CLARION subsystems. |
static int |
ACS_CL
|
static int |
ACS_GAUGE
|
static int |
ACS_IN_DIM
|
static int |
ACS_IN_VAL
|
static int |
ACS_LEARN
|
static int |
ACS_OUT_DIM
|
static int |
ACS_OUT_VAL
|
static int |
ACS_PARAM
|
static int |
ACS_PERFORM
|
static int |
ACS_REASON
|
static int |
ACS_SAMPLE_NUM
|
static int |
AMN_PASS
|
static int |
ASSOC_APP
|
static int |
ASSOC_WGT_C
|
static int |
ASSOC_WGT_R
|
static int |
AT_TL
|
static int |
BL_RT
|
static int |
BUR
|
static int |
CHUNK_RETR
|
static int |
DATA_TYPE
|
static int |
DRIVE
|
static int |
DRV_REP
|
static int |
DT_TL
|
static int |
ELIG
|
static int |
EX_CHUNK
|
static int |
EX_RULE
|
static int |
FR_ACT
|
static int |
FR_CON
|
static int |
FR_UTL
|
static int |
FR_WGT_C
|
static int |
FR_WGT_R
|
protected Global |
global
the associated Global object. |
static int |
GOAL
|
static int |
GOAL_DIM
|
static int |
GOAL_SETTING
|
static int |
IRL_IG
|
static int |
IRL_PARAM
|
static int |
IRL_POS
|
static int |
IRL_UTL
|
static int |
IRL_WGT_C
|
static int |
IRL_WGT_R
|
static int |
MCS
constants for CLARION subsystems. |
static int |
MCS_SAMPLE_NUM
|
static int |
NACS
constants for CLARION subsystems. |
static int |
NACS_GAUGE
|
static int |
NACS_IN_DIM
|
static int |
NACS_IN_VAL
|
static int |
NACS_LEARN
|
static int |
NACS_OUT_DIM
|
static int |
NACS_OUT_VAL
|
static int |
NACS_PARAM
|
static int |
NACS_PERFORM
|
static int |
NACS_REASON
|
static int |
NACS_SAMPLE_NUM
|
static int |
OVER_RT
|
static int |
PT_TL
|
static int |
REIN
|
static int |
REIN_FUNC
|
static int |
RER_IG
|
static int |
RER_POS
|
static int |
RER_UTL
|
static int |
RER_WGT_C
|
static int |
RER_WGT_R
|
static int |
RT
constants for CLARION subsystems. |
static int |
RT_SAMPLE_NUM
|
static int |
SIM
|
static int |
SUB_SYS_NUM
constants for CLARION subsystems. |
static int |
TDG
|
static int |
TL_RT
|
Constructor Summary | |
TaskClarion()
|
Method Summary | |
void |
combineByBottomUpRectification()
bottom-up rectification process described in the Chapter on ACS in tutorial. |
void |
combineByTopDownGuidance()
top-down guidance process described in the Chapter on ACS in tutorial. |
double |
decideFrAction(int groupIdx,
int netIdx,
int setIdx,
Feature[] sensoryInput,
GoalChunk gsItem,
Chunk[] wmItems,
short[][][] suggestedAction)
Decides action by a Fixed Rule. |
short[] |
getAamDataPattern(int netIdx,
int chunkIdx,
int ruleIdx)
Returns the types of data pettern for training AAM. |
int |
getAmnPassTime()
Returns AMN one-pass time. |
int |
getAssocAppTime(double assocRuleBla)
Returns associative rule application time. |
double[] |
getAssocDimWeights(int dimNum)
Returns the weights for computing associative rule support from one condition chunk. |
double[] |
getAssocWeights(int condNum)
Returns the weights for computing associative rule support from all of the condition chunks. |
int |
getAT_TL(boolean flag,
int assocAppTime,
int chunkRetrTime)
Returns the Top-Level Actuation Time. |
int |
getBLOverallRT(int PT_BL,
int DT_BL,
int AT_BL)
Returns the overall Bottom Level response time computed by the formula use defines. |
int |
getChunkRetrTime(double chunkBla)
Returns the NACS chunk retrieval time. |
int |
getDT_TL(int DT_BL,
int actionTime,
double ruleBla,
double chunkBla)
Returns the Top-Level Decision Time. |
short[][][] |
getEligibility(int netIdx)
Returns the eligible conditions of the specified network. |
static java.lang.String |
getExplanation(int subSysIdx,
int sampleIdx)
|
GKSChunk[] |
getExternalNacsChunks()
Returns the externally given NACS chunks. |
AssocRule[] |
getExternalNacsRules()
Returns the externally given associative rules. |
short[][][] |
getFrAction(int groupIdx,
int netIdx,
int ruleIdx)
Returns FR actions. |
short[][] |
getFrCondition(int groupIdx,
int netIdx,
int ruleIdx)
Returns a FR condition. |
boolean |
getFrPositivity(int learnOption,
double reward,
double qDiscount,
double newMaxQVal,
double qVal,
double threshold)
Returns true if current step is positive or not according to FR positivity criterion, false otherwise. |
double |
getFrUtility(int netIdx,
int setIdx,
double PM,
double NM)
Returns the utility of a specified set of FR rules. |
double[] |
getFrWeights(int netIdx)
Returns the FR dimensional weights used to calculate rule support. |
short[] |
getGoalDimDVs()
Returns the goal dimension-value info. |
short[][] |
getGoals()
Returns the goals. |
double |
getIrlIG(int netIdx,
double PM,
double NM,
double threshold)
Returns the Information Gain according to the IRL Information Gain criterion. |
boolean |
getIrlPositivity(int learnOption,
double reward,
double qDiscount,
double newMaxQVal,
double qVal,
double threshold)
Returns true if current step is positive or not according to IRL positivity criterion, false otherwise. |
IrlRuleForm |
getIrlRule(int groupIdx,
int netIdx,
int setIdx,
int ruleIdx)
Returns an IRL rule form corresponding to the rule index. |
double |
getIrlUtility(int netIdx,
int setIdx,
double PM,
double NM)
Returns the utility of a specified set of IRL rules. |
double[] |
getIrlWeights(int netIdx)
Returns the IRL dimensional weights used to calculate rule support. |
java.lang.Object[] |
getNacsResults()
new routine. |
int |
getOverallRT(int RT_BL,
int RT_TL)
Returns the overall response time computed by the formula use defines. |
int |
getPT_TL(int PT_BL)
Returns Top-Level Perceptual Time. |
double |
getReinforcement(int netIdx,
Feature[] input,
Chunk[] wmItems,
GoalChunk goalItem,
short[][][] action,
Feature[] newInput,
Chunk[] newWmItems,
GoalChunk newGoalItem)
Returns the reinforcement of the specified ACS network. |
double |
getRerIG(int netIdx,
double PMa,
double NMa,
double PMb,
double NMb)
Returns the Information Gain according to the RER Information Gain criterion. |
boolean |
getRerPositivity(int learnOption,
double reward,
double qDiscount,
double newMaxQVal,
double qVal,
double threshold)
Returns true if current step is positive or not according to RER positivity criterion, false otherwise. |
double |
getRerUtility(int netIdx,
int setIdx,
double PM,
double NM)
Returns the utility of a specified set of RER rules. |
double[] |
getRerWeights(int netIdx)
Returns the RER dimensional weights used to calculate rule support. |
static java.lang.String |
getSample(int subSysIdx,
int sampleIdx)
Returns the specified sample code. |
double |
getSimilarity(GKSChunk chunk1,
GKSChunk chunk2)
Returns the similarity between two chunks. |
int |
getTLOverallRT(int PT_TL,
int DT_TL,
int AT_TL)
Returns the overall Top Level response time computed by the formula use defines. |
void |
performEncodeExternalKnowledge(short[][] action)
new routine. |
void |
performNacsAssimilation(short[][] action)
new routine. |
void |
setGlobal(Global global)
|
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Field Detail |
public static final int SUB_SYS_NUM
public static final int ACS
public static final int NACS
public static final int RT
public static final int MCS
public static final int ACS_SAMPLE_NUM
public static final int NACS_SAMPLE_NUM
public static final int RT_SAMPLE_NUM
public static final int MCS_SAMPLE_NUM
public static final int GOAL
public static final int GOAL_DIM
public static final int BUR
public static final int TDG
public static final int ELIG
public static final int REIN
public static final int RER_WGT_C
public static final int RER_WGT_R
public static final int RER_UTL
public static final int RER_POS
public static final int RER_IG
public static final int IRL_WGT_C
public static final int IRL_WGT_R
public static final int IRL_UTL
public static final int IRL_POS
public static final int IRL_IG
public static final int IRL_PARAM
public static final int FR_WGT_C
public static final int FR_WGT_R
public static final int FR_UTL
public static final int FR_CON
public static final int FR_ACT
public static final int EX_CHUNK
public static final int EX_RULE
public static final int ASSOC_WGT_C
public static final int ASSOC_WGT_R
public static final int SIM
public static final int DATA_TYPE
public static final int OVER_RT
public static final int BL_RT
public static final int TL_RT
public static final int PT_TL
public static final int DT_TL
public static final int AT_TL
public static final int ASSOC_APP
public static final int CHUNK_RETR
public static final int AMN_PASS
public static final int DRIVE
public static final int DRV_REP
public static final int REIN_FUNC
public static final int GOAL_SETTING
public static final int ACS_IN_DIM
public static final int NACS_IN_DIM
public static final int ACS_OUT_DIM
public static final int NACS_OUT_DIM
public static final int ACS_IN_VAL
public static final int NACS_IN_VAL
public static final int ACS_OUT_VAL
public static final int NACS_OUT_VAL
public static final int ACS_LEARN
public static final int NACS_LEARN
public static final int ACS_REASON
public static final int NACS_REASON
public static final int ACS_CL
public static final int ACS_PARAM
public static final int NACS_PARAM
public static final int ACS_PERFORM
public static final int NACS_PERFORM
public static final int ACS_GAUGE
public static final int NACS_GAUGE
protected Global global
Constructor Detail |
public TaskClarion()
Method Detail |
public static java.lang.String getSample(int subSysIdx, int sampleIdx)
subSysIdx
- the index on CLARION subsystem.sampleIdx
- the index on the sample within the specified subsystem.
public static java.lang.String getExplanation(int subSysIdx, int sampleIdx)
public void setGlobal(Global global)
public short[][] getGoals()
public short[] getGoalDimDVs()
public void combineByBottomUpRectification()
public void combineByTopDownGuidance()
public short[][][] getEligibility(int netIdx)
netIdx
- the ACS network NO.
public double getReinforcement(int netIdx, Feature[] input, Chunk[] wmItems, GoalChunk goalItem, short[][][] action, Feature[] newInput, Chunk[] newWmItems, GoalChunk newGoalItem)
netIdx
- the network NO.input
- current input,action
- current action.newInput
- new input resulting from firing the action.
public double[] getRerWeights(int netIdx)
netIdx
- the ACS network NO.
public double getRerUtility(int netIdx, int setIdx, double PM, double NM)
netIdx
- the network NO.setIdx
- the rule subset NO.PM
- Positive Match of the rule, equals the number of times
that an input state matches rule condition, rule action is performed
and the result is positive.NM
- Negative Match of the rule, equals the number of times
that an input state matches rule condition, rule action is performed
and the result is negative.
public boolean getRerPositivity(int learnOption, double reward, double qDiscount, double newMaxQVal, double qVal, double threshold)
learnOption
- learning method.reward
- currently received reward.qDiscount
- the discount factor for Q-Learning that favors
reinfocement received sooner relative to that received later.
used in q-learning method.newMaxQVal
- maximum Q-value of the new state resuling from
current action in current state, Q(next state, next possible action).
used in q-learning method.qVal
- current q-value, Q(current state, current action).threshold
- the threshold for rule positivity.
public double getRerIG(int netIdx, double PMa, double NMa, double PMb, double NMb)
netIdx
- the network NO. decdies the values of c1 and c2.PMa
- Positive Match of the rule a, equals the number of times
that an input state matches rule condition, rule action is performed
and the result is positive.NMa
- Negative Match of the rule a, equals the number of times
that an input state matches rule condition, rule action is performed
and the result is negative.PMb
- Positive Match of the rule b.NMb
- Negative Match of the rule b.
public double[] getIrlWeights(int netIdx)
netIdx
- the ACS network NO.
public double getIrlUtility(int netIdx, int setIdx, double PM, double NM)
netIdx
- the network NO.setIdx
- the rule subset NO.PM
- Positive Match of the rule, equals the number of times
that an input state matches rule condition, rule action is performed
and the result is positive.NM
- Negative Match of the rule, equals the number of times
that an input state matches rule condition, rule action is performed
and the result is negative.
public boolean getIrlPositivity(int learnOption, double reward, double qDiscount, double newMaxQVal, double qVal, double threshold)
learnOption
- learning method.reward
- currently received reward.qDiscount
- the discount factor for Q-Learning that favors
reinfocement received sooner relative to that received later.
used in q-learning method.newMaxQVal
- maximum Q-value of the new state resuling from
current action in current state, Q(next state, next possible action).
used in q-learning method.qVal
- current q-value, Q(current state, current action).threshold
- the threshold for rule positivity.
public double getIrlIG(int netIdx, double PM, double NM, double threshold)
netIdx
- the network NO. decdies the values of c5 and c6.PM
- Positive Match of the rule, equals the number of times
that an input state matches rule condition, rule action is performed
and the result is positive.NM
- Negative Match of the rule, equals the number of times
that an input state matches rule condition, rule action is performed
and the result is negative.threshold
- compared threshold value.
public IrlRuleForm getIrlRule(int groupIdx, int netIdx, int setIdx, int ruleIdx)
groupIdx
- agent group index.netIdx
- ACS network index.setIdx
- rule subset index.ruleIdx
- rule index.
public double[] getFrWeights(int netIdx)
netIdx
- the ACS network NO.
public double getFrUtility(int netIdx, int setIdx, double PM, double NM)
netIdx
- the network NO.setIdx
- the rule subset NO.PM
- Positive Match of the rule, equals the number of times
that an input state matches rule condition, rule action is performed
and the result is positive.NM
- Negative Match of the rule, equals the number of times
that an input state matches rule condition, rule action is performed
and the result is negative.
public boolean getFrPositivity(int learnOption, double reward, double qDiscount, double newMaxQVal, double qVal, double threshold)
learnOption
- learning method.reward
- currently received reward.qDiscount
- the discount factor for Q-Learning that favors
reinfocement received sooner relative to that received later.
used in q-learning method.newMaxQVal
- maximum Q-value of the new state resuling from
current action in current state, Q(next state, next possible action).
used in q-learning method.qVal
- current q-value, Q(current state, current action).threshold
- the threshold for rule positivity.
public short[][] getFrCondition(int groupIdx, int netIdx, int ruleIdx)
groupIdx
- agent group index.netIdx
- ACS network index.ruleIdx
- rule index.
public short[][][] getFrAction(int groupIdx, int netIdx, int ruleIdx)
groupIdx
- learniing group the agent is in.netIdx
- the net index.ruleIdx
- the rule index.
public double decideFrAction(int groupIdx, int netIdx, int setIdx, Feature[] sensoryInput, GoalChunk gsItem, Chunk[] wmItems, short[][][] suggestedAction)
groupIdx
- learniing group the agent is in.netIdx
- the net index.setIdx
- the rule set index.sensoryInput
- current sensory input.gsItem
- the top goal item.wmItems
- current WM content.
public GKSChunk[] getExternalNacsChunks()
public AssocRule[] getExternalNacsRules()
public double[] getAssocWeights(int condNum)
public double[] getAssocDimWeights(int dimNum)
public double getSimilarity(GKSChunk chunk1, GKSChunk chunk2)
chunk1
- the source chunk.chunk2
- the destination chunk.
public short[] getAamDataPattern(int netIdx, int chunkIdx, int ruleIdx)
netIdx
- the AAM net index.chunkIdx
- the chunk the rule is associated with.ruleIdx
- the rule index on the rule group associated with the chunk.
public void performEncodeExternalKnowledge(short[][] action)
public void performNacsAssimilation(short[][] action)
public java.lang.Object[] getNacsResults()
public int getOverallRT(int RT_BL, int RT_TL)
RT_BL
- response time from Bottom Level.RT_TL
- response time from Top Level.
public int getBLOverallRT(int PT_BL, int DT_BL, int AT_BL)
PT_BL
- Bottom-Level Perceptual Time.DT_BL
- Bottom-Level Decision Time.AT_BL
- Bottom-Level Actuation Time.
public int getTLOverallRT(int PT_TL, int DT_TL, int AT_TL)
public int getPT_TL(int PT_BL)
PT_BL
- Bottom-Level Perceptual Time.
public int getDT_TL(int DT_BL, int actionTime, double ruleBla, double chunkBla)
DT_BL
- Bottom-Level Decision Time.actionTime
- time determined by the operation dictated by
a particular rule.ruleBla
- rule base-level activation.chunkBla
- action chunk base-level activation.
public int getAT_TL(boolean flag, int assocAppTime, int chunkRetrTime)
flag
- decides if NACS is involved or not.assocAppTime
- time of one iteration of associative applicaiton.chunkRetrTime
- time of one iteration of chunk retrieval.public int getAssocAppTime(double assocRuleBla)
assocRuleBla
- associative rule base-level activation.
public int getChunkRetrTime(double chunkBla)
chunkBla
- - nacs chunk base-level activation.
public int getAmnPassTime()
|
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