tepichord/GEMLA
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions

Discerning between mainline and offshoot

Browse source
This commit is contained in:
vandomej 2024-04-09 15:05:14 -07:00
parent 822df77f62
commit e2be40c318
2 changed files with 34 additions and 16 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

1
analyze_data.py
View file

@ -129,6 +129,7 @@ for node in right_nodes:
for i in range(len(node_scores)):
for (individual, score) in node_scores[i].items():
translated_node_scores.append((node["val"]["id"], i, score))
scores.append(translated_node_scores)
# Organize scores by individual and then by generation
individual_generation_scores = defaultdict(lambda: defaultdict(list))

49
gemla/src/bin/fighter_nn/mod.rs
View file

@ -40,6 +40,8 @@ const NEURAL_NETWORK_INITIAL_WEIGHT_MIN: f32 = -2.0;
const NEURAL_NETWORK_INITIAL_WEIGHT_MAX: f32 = 2.0;
const NEURAL_NETWORK_CROSSBREED_SEGMENTS_MIN: usize = 2;
const NEURAL_NETWORK_CROSSBREED_SEGMENTS_MAX: usize = 20;
const OFFSHOOT_GENERATIONAL_LENIENCE: u64 = 5;
const MAINLINE_GENERATIONAL_LENIENCE: u64 = 20;
const SIMULATION_ROUNDS: usize = 5;
const SURVIVAL_RATE: f32 = 0.5;
@ -74,6 +76,7 @@ pub struct FighterNN {
// Shows how individuals are mapped from one generation to the next
pub id_mapping: Vec<HashMap<u64, u64>>,
pub lerp_amount: f32,
pub generational_lenience: u64,
}
#[async_trait]
@ -158,6 +161,7 @@ impl GeneticNode for FighterNN {
mutation_weight_range: -mutation_weight_amplitude..mutation_weight_amplitude,
id_mapping: vec![HashMap::new()],
lerp_amount: 0.0,
generational_lenience: OFFSHOOT_GENERATIONAL_LENIENCE,
}))
}
@ -186,6 +190,18 @@ impl GeneticNode for FighterNN {
};
let secondary_id = loop {
if allotted_simulations.is_empty() {
// Select a random id
let random_id = loop {
let id = thread_rng().gen_range(0..self.population_size);
if id != primary_id {
break id;
}
};
break random_id;
}
let id = thread_rng().gen_range(0..allotted_simulations.len());
let (i, _) = allotted_simulations[id];
@ -294,7 +310,7 @@ impl GeneticNode for FighterNN {
self.scores.push(scores);
Ok(should_continue(&self.scores)?)
Ok(should_continue(&self.scores, self.generational_lenience)?)
}
async fn mutate(&mut self, _context: GeneticNodeContext<Self::Context>) -> Result<(), Error> {
@ -644,6 +660,7 @@ impl GeneticNode for FighterNN {
mutation_weight_range,
id_mapping: vec![HashMap::new()],
lerp_amount,
generational_lenience: MAINLINE_GENERATIONAL_LENIENCE,
}))
}
}
@ -654,8 +671,8 @@ impl FighterNN {
}
}
fn should_continue(scores: &[HashMap<u64, f32>]) -> Result<bool, Error> {
if scores.len() < 5 {
fn should_continue(scores: &[HashMap<u64, f32>], lenience: u64) -> Result<bool, Error> {
if scores.len() < lenience as usize {
return Ok(true);
}
@ -691,8 +708,8 @@ fn should_continue(scores: &[HashMap<u64, f32>]) -> Result<bool, Error> {
}
let highest_generation_index = scores.len() - 1;
let result = highest_generation_index - generation_with_highest_q3 < 5
&& highest_generation_index - generation_with_highest_median < 5;
let result = highest_generation_index - generation_with_highest_q3 < lenience as usize
&& highest_generation_index - generation_with_highest_median < lenience as usize;
debug!(
"Highest Q3 value: {} at generation {}, Highest Median value: {} at generation {}, Continuing? {}",
@ -1534,57 +1551,57 @@ pub mod test {
.collect();
assert!(
should_continue(scores[..0].as_ref())
should_continue(scores[..0].as_ref(), 5)
.expect("Failed to determine if the simulation should continue")
== true
);
assert!(
should_continue(scores[..1].as_ref())
should_continue(scores[..1].as_ref(), 5)
.expect("Failed to determine if the simulation should continue")
== true
);
assert!(
should_continue(scores[..2].as_ref())
should_continue(scores[..2].as_ref(), 5)
.expect("Failed to determine if the simulation should continue")
== true
);
assert!(
should_continue(scores[..3].as_ref())
should_continue(scores[..3].as_ref(), 5)
.expect("Failed to determine if the simulation should continue")
== true
);
assert!(
should_continue(scores[..4].as_ref())
should_continue(scores[..4].as_ref(), 5)
.expect("Failed to determine if the simulation should continue")
== true
);
assert!(
should_continue(scores[..5].as_ref())
should_continue(scores[..5].as_ref(), 5)
.expect("Failed to determine if the simulation should continue")
== true
);
assert!(
should_continue(scores[..6].as_ref())
should_continue(scores[..6].as_ref(), 5)
.expect("Failed to determine if the simulation should continue")
== true
);
assert!(
should_continue(scores[..7].as_ref())
should_continue(scores[..7].as_ref(), 5)
.expect("Failed to determine if the simulation should continue")
== true
);
assert!(
should_continue(scores[..8].as_ref())
should_continue(scores[..8].as_ref(), 5)
.expect("Failed to determine if the simulation should continue")
== false
);
assert!(
should_continue(scores[..9].as_ref())
should_continue(scores[..9].as_ref(), 5)
.expect("Failed to determine if the simulation should continue")
== false
);
assert!(
should_continue(scores[..10].as_ref())
should_continue(scores[..10].as_ref(), 5)
.expect("Failed to determine if the simulation should continue")
== false
);