MABEAM Phase 4: Advanced Coordination (Foundation.MABEAM.Coordination.*)
Phase Overview
Goal: Implement sophisticated coordination strategies (auction, market-based) Duration: 5-6 development cycles Prerequisites: Phase 3 complete (Basic coordination operational)
Phase 4 Architecture
Foundation.MABEAM.Coordination.*
├── Auction-Based Coordination
├── Market-Based Coordination
├── Game-Theoretic Protocols
├── Adaptive Coordination
└── Performance Optimization
Step-by-Step Implementation
Step 4.1: Auction-Based Coordination
Duration: 2 development cycles Checkpoint: Multiple auction types working with no warnings
Objectives
- Implement sealed-bid auctions
- English (ascending) auctions
- Dutch (descending) auctions
- Combinatorial auctions
- Payment rules and efficiency metrics
TDD Approach
Red Phase: Create auction tests
# test/foundation/mabeam/coordination/auction_test.exs
defmodule Foundation.MABEAM.Coordination.AuctionTest do
use ExUnit.Case, async: false
alias Foundation.MABEAM.Coordination.Auction
describe "sealed bid auction" do
test "first price sealed bid auction" do
bids = [
{agent1: %{bid: 10.0, value: 0.8}},
{agent2: %{bid: 15.0, value: 0.9}},
{agent3: %{bid: 12.0, value: 0.7}}
]
{:ok, result} = Auction.run_auction(:temperature_setting, bids,
auction_type: :sealed_bid,
payment_rule: :first_price
)
assert result.winner == :agent2
assert result.winning_value == 0.9
assert result.payment == 15.0
end
test "second price sealed bid auction" do
bids = [
{agent1: %{bid: 10.0, value: 0.8}},
{agent2: %{bid: 15.0, value: 0.9}},
{agent3: %{bid: 12.0, value: 0.7}}
]
{:ok, result} = Auction.run_auction(:resource_allocation, bids,
auction_type: :sealed_bid,
payment_rule: :second_price
)
assert result.winner == :agent2
assert result.payment == 12.0 # Second highest bid
end
end
describe "english auction" do
test "ascending price auction with multiple rounds" do
agents = [:bidder1, :bidder2, :bidder3]
{:ok, result} = Auction.run_auction(:cpu_allocation, agents,
auction_type: :english,
starting_price: 5.0,
increment: 1.0,
max_rounds: 10
)
assert result.auction_type == :english
assert result.payment >= 5.0
assert result.rounds <= 10
end
end
end
Green Phase: Implement auction mechanisms
# lib/foundation/mabeam/coordination/auction.ex
defmodule Foundation.MABEAM.Coordination.Auction do
@moduledoc """
Auction-based coordination where agents bid for resources or parameter values.
"""
alias Foundation.MABEAM.{AgentRegistry, Types}
alias Foundation.{Events, Telemetry}
@type bid :: {atom(), bid_details()}
@type bid_details :: %{
bid: float(),
value: term(),
max_bid: float(),
reason: String.t()
}
@type auction_result :: %{
winner: atom(),
winning_value: term(),
payment: float(),
auction_type: auction_type(),
participants: non_neg_integer(),
efficiency: float(),
rounds: non_neg_integer()
}
@type auction_type :: :sealed_bid | :english | :dutch | :combinatorial
@spec run_auction(atom(), [bid()], keyword()) :: {:ok, auction_result()} | {:error, term()}
def run_auction(variable_id, bids, opts \\ [])
def run_auction(variable_id, bids, opts) do
auction_type = Keyword.get(opts, :auction_type, :sealed_bid)
start_time = System.monotonic_time()
emit_auction_start_event(variable_id, auction_type, length(bids))
result = case auction_type do
:sealed_bid -> run_sealed_bid_auction(variable_id, bids, opts)
:english -> run_english_auction(variable_id, bids, opts)
:dutch -> run_dutch_auction(variable_id, bids, opts)
:combinatorial -> run_combinatorial_auction(variable_id, bids, opts)
end
emit_auction_complete_event(variable_id, result, start_time)
result
end
# Implementation of different auction types...
end
Deliverables
- Complete auction framework
- Multiple auction types implemented
- Payment rules and efficiency calculations
- Comprehensive auction testing
Step 4.2: Market-Based Coordination
Duration: 2 development cycles
Checkpoint: Market mechanisms working with price discovery
Objectives
- Implement market-based resource allocation
- Price discovery mechanisms
- Supply and demand modeling
- Market equilibrium finding
TDD Approach
Red Phase: Test market mechanisms
describe "market coordination" do
test "finds market equilibrium" do
suppliers = [
{cpu_supplier: %{supply: 100, min_price: 1.0}},
{memory_supplier: %{supply: 200, min_price: 0.5}}
]
demanders = [
{compute_agent: %{demand: 80, max_price: 2.0}},
{storage_agent: %{demand: 150, max_price: 1.0}}
]
{:ok, result} = Market.find_equilibrium(:resource_market, suppliers, demanders)
assert result.equilibrium_found == true
assert result.clearing_price > 0
assert result.total_traded > 0
end
end
Deliverables
- Market-based coordination framework
- Price discovery algorithms
- Supply/demand modeling
- Equilibrium finding mechanisms
Step 4.3: Game-Theoretic Protocols
Duration: 1-2 development cycles Checkpoint: Basic game theory implementations
Objectives
- Nash equilibrium finding
- Mechanism design principles
- Incentive compatibility
- Strategy-proof mechanisms
Deliverables
- Game-theoretic coordination protocols
- Nash equilibrium algorithms
- Mechanism design framework
- Strategy analysis tools
Phase 4 Completion Criteria
Functional Requirements
- Advanced coordination mechanisms operational
- Auction systems working with multiple types
- Market-based coordination functional
- Game-theoretic protocols implemented
- Performance optimization complete
Quality Requirements
- Zero dialyzer warnings
- Zero credo –strict violations
- >95% test coverage
- Performance benchmarks for all mechanisms
- Scalability testing completed
Next Phase
Upon successful completion of Phase 4:
- Proceed to Phase 5: Telemetry and Monitoring
- Begin with
MABEAM_PHASE_05_TELEMETRY.md