# Advanced Policy Configuration - Showcasing improvements over charge-lnd
# This configuration uses all the advanced features including machine learning

[default]
final = false
base_fee_msat = 0
fee_ppm = 1000
time_lock_delta = 80
enable_auto_rollback = true
rollback_threshold = 0.25
learning_enabled = true

[revenue-maximization]
# High-value channels with learning enabled
chan.min_capacity = 10000000
activity.level = high, medium
strategy = revenue_max
learning_enabled = true
enable_auto_rollback = true
rollback_threshold = 0.2
priority = 5

[competitive-pricing]
# Channels where we compete with many alternatives - use inbound discounts
network.min_alternatives = 5
peer.fee_ratio.min = 0.7
peer.fee_ratio.max = 1.3
strategy = inbound_discount
fee_ppm = 1200
inbound_fee_ppm = -75
inbound_base_fee_msat = -300
priority = 10

[premium-peers]
# Special rates for known high-value peers (replace with actual pubkeys)
node.id = 033d8656219478701227199cbd6f670335c8d408a92ae88b962c49d4dc0e83e025, 03cde60a6323f7122d5178255766e38114b4722ede08f7c9e0c5df9b912cc201d6
strategy = static
fee_ppm = 750
inbound_fee_ppm = -50
inbound_base_fee_msat = -250
enable_auto_rollback = false
priority = 5

[flow-based-optimization]
# Channels with good flow patterns - optimize based on activity
flow.7d.min = 5000000
strategy = flow_based
learning_enabled = true
enable_auto_rollback = true
rollback_threshold = 0.3
priority = 15

[balance-extreme-drain]
# Very unbalanced channels (>90% local) - aggressive rebalancing
chan.min_ratio = 0.9
strategy = balance_based
fee_ppm = 100
inbound_fee_ppm = -200
inbound_base_fee_msat = -1000
max_fee_ppm = 300
priority = 8

[balance-extreme-preserve]
# Very low balance channels (<10% local) - aggressive preservation
chan.max_ratio = 0.1
strategy = balance_based
fee_ppm = 3000
inbound_fee_ppm = 100
inbound_base_fee_msat = 500
min_fee_ppm = 2000
priority = 8

[small-channel-activation]
# Small channels that are inactive - make them competitive
chan.max_capacity = 1000000
activity.level = inactive, low
strategy = static
fee_ppm = 150
inbound_fee_ppm = -100
max_fee_ppm = 400
priority = 25

[large-inactive-penalty]
# Large but inactive channels - higher fees to encourage closure or activation
chan.min_capacity = 5000000
activity.level = inactive
strategy = static
fee_ppm = 2500
inbound_fee_ppm = 50
min_fee_ppm = 2000
priority = 20

[medium-flow-optimization]
# Medium activity channels - gradual optimization
activity.level = medium
flow.7d.min = 1000000
flow.7d.max = 10000000
strategy = proportional
fee_ppm = 1200
inbound_fee_ppm = -25
learning_enabled = true
priority = 30

[old-channels]
# Channels older than 90 days - conservative management
chan.min_age_days = 90
strategy = static
fee_ppm = 800
inbound_fee_ppm = -10
enable_auto_rollback = false
priority = 35

[new-channels]
# Channels younger than 7 days - give time to establish flow
chan.max_age_days = 7
strategy = static
fee_ppm = 500
inbound_fee_ppm = -50
max_fee_ppm = 1000
priority = 12

[discourage-routing]
# Channels we want to discourage (e.g., poorly connected peers)
chan.max_ratio = 0.05
chan.min_capacity = 1000000
strategy = static
fee_ppm = 5000
inbound_fee_ppm = 200
min_fee_ppm = 4000
priority = 90

[catch-all]
# Final policy with learning enabled
strategy = revenue_max
fee_ppm = 1000
inbound_fee_ppm = 0
learning_enabled = true
enable_auto_rollback = true
rollback_threshold = 0.3
priority = 100