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package Sim::AgentSoar::Engine; |
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use strict; |
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use warnings; |
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422
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our $VERSION = '0.06'; |
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our @ALLOWED_OPERATORS = qw( |
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add_1 |
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sub_1 |
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add_3 |
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sub_3 |
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mul_2 |
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div_2_if_even |
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); |
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our $MIN_VALUE = -100; |
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our $MAX_VALUE = 100; |
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sub allowed_operators |
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{ |
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return @ALLOWED_OPERATORS; |
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} |
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sub apply_operator |
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{ |
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my ($class, $value, $op) = @_; |
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return $value + 1 if $op eq 'add_1'; |
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0
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return $value - 1 if $op eq 'sub_1'; |
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return $value + 3 if $op eq 'add_3'; |
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return $value - 3 if $op eq 'sub_3'; |
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return $value * 2 if $op eq 'mul_2'; |
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0
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if ($op eq 'div_2_if_even') |
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{ |
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return undef unless $value % 2 == 0; |
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return int($value / 2); |
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} |
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0
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return undef; |
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} |
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sub valid_value |
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{ |
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my ($class, $value) = @_; |
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return defined($value) |
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&& $value >= $MIN_VALUE |
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&& $value <= $MAX_VALUE; |
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} |
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sub metric |
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{ |
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my ($class, $value, $target) = @_; |
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return abs($value - $target); |
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} |
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59
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1; |
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61
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62
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=pod |
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63
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64
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=head1 NAME |
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65
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66
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Sim::AgentSoar::Engine - Deterministic calibration environment for heuristic AgentSoar |
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68
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=head1 DESCRIPTION |
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69
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70
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Sim::AgentSoar::Engine defines a minimal deterministic environment used to |
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71
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calibrate and evaluate the Sim::AgentSoar architecture. |
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72
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73
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The domain consists of integer reachability under a fixed set of operators. |
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Although simple, it is intentionally chosen to expose core AgentSoar dynamics: |
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76
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=over 4 |
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77
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78
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=item * Local vs. global improvement tension |
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80
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=item * Reversible and irreversible operations |
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81
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82
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=item * Potential regression |
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83
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84
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=item * Cycles and repetition |
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85
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86
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=item * Heuristic bias evaluation |
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88
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=back |
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This module contains no probabilistic logic and no LLM interaction. |
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All state transitions and evaluations are deterministic. |
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93
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=head2 Domain Definition |
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95
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State: |
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value => integer |
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Operators: |
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101
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add_1 |
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102
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sub_1 |
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103
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add_3 |
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104
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sub_3 |
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105
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mul_2 |
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106
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div_2_if_even |
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107
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108
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Evaluation metric: |
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109
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110
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abs(value - target) |
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112
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Domain bounds: |
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114
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-100 <= value <= 100 |
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116
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=head2 Purpose |
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118
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The integer domain serves as: |
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120
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=over 4 |
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122
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=item * A calibration environment for testing heuristic quality |
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124
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=item * A controlled benchmark for branching and correction logic |
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126
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=item * A deterministic substrate for measuring LLM efficiency |
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128
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=item * A regression testing environment for architectural changes |
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130
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=back |
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132
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Because the environment is fully observable and inexpensive to evaluate, |
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it allows clear separation between structural AgentSoar performance and |
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heuristic proposal behavior. |
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136
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=head2 ReAgentSoar Role |
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138
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In the broader reAgentSoar program, this module acts as: |
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140
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=over 4 |
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142
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=item * A wind-tunnel model for cognitive architecture experiments |
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144
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=item * A baseline for comparing deterministic and LLM-guided AgentSoar |
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146
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=item * A controlled testbed for future memory-layer extensions |
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148
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=back |
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150
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The simplicity of the domain is intentional: it isolates architectural |
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effects from domain complexity. |
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153
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=head1 METHODS |
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155
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=head2 allowed_operators |
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157
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Returns the list of valid operators. |
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158
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159
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=head2 apply_operator |
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161
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Applies an operator to a state value. |
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163
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=head2 valid_value |
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165
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Ensures state remains within domain bounds. |
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167
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=head2 metric |
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168
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169
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Computes distance to target. |
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170
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171
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=head1 AUTHOR |
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173
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Gian Luca Brunetti (2026), gianluca.brunetti@gmail.com |
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175
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=cut |
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