Quan'ta've Argumenta'on Debates A. Rago 1 , F. Toni 1 , M. - PowerPoint PPT Presentation

Discon'nuity-Free Decision Support with Quan'ta've Argumenta'on Debates A. Rago 1 , F. Toni 1 , M. Aurisicchio 1 & P. Baroni 2 1. Imperial College London 2. Universita` degli Studi di Brescia Cardiff Argumenta'on Forum 6 th July 2016 Discon'nuity-Free Decision Support with Quan'ta've Argumenta'on Debates 1 / 24 A. Rago, F. Toni, M. Aurisicchio & P. Baroni

Presenta'on Overview 1. Background • IBIS Charts and QuAD Frameworks • QuAD Algorithm/Seman'cs 2. Research Summary • Mo'va'on for DF-QuAD • DF-QuAD Algorithm • Comparison of the DF-QuAD and QuAD Algorithms • Proper'es Not Held by QuAD • Proper'es Shared with QuAD • Rela'onship to Abstract Argumenta'on • Reverse Engineering Func'onality • Applica'ons of QuAD Frameworks 3. Future Work 4. Conclusions Discon'nuity-Free Decision Support with Quan'ta've Argumenta'on Debates 2 / 24 A. Rago, F. Toni, M. Aurisicchio & P. Baroni

Background – IBIS Charts & QuAD Frameworks IBIS (Issue Based Informa'on System) charts [Kunz and Ri_el, 1970] . • • QuAD (Quan'ta've Argumenta'on Debate) frameworks [Baroni et al. 2015] . – Special types of IBIS trees with base scores for nodes. QuAD Framework [www.arganddec.com] Discon'nuity-Free Decision Support with Quan'ta've Argumenta'on Debates 3 / 24 A. Rago, F. Toni, M. Aurisicchio & P. Baroni

Background – IBIS Charts & QuAD Frameworks IBIS (Issue Based Informa'on System) charts [Kunz and Ri_el, 1970] . • • QuAD (Quan'ta've Argumenta'on Debate) frameworks [Baroni et al. 2015] . – Special types of IBIS trees with base scores for nodes. • Correspond to BAFs (Bipolar Argumenta'on Frameworks) [Cayrol and Lagasquie-Schiex, 2005] . QuAD Framework [www.arganddec.com] BAF Framework A1 A2 + + - + C1 P1 P2 P3 - - - C2 C3 C4 Discon'nuity-Free Decision Support with Quan'ta've Argumenta'on Debates 3 / 24 A. Rago, F. Toni, M. Aurisicchio & P. Baroni

Background – QuAD Algorithm/Seman'cs Base scores are used by the QuAD algorithm to calculate each node’s overall strength . • • Base scores and strengths are in [0,1]. • Strength is a form of gradual acceptance [Cayrol and Lagasquie-Schiex, 2005] . Discon'nuity-Free Decision Support with Quan'ta've Argumenta'on Debates 4 / 24 A. Rago, F. Toni, M. Aurisicchio & P. Baroni

Background – QuAD Algorithm/Seman'cs Base scores are used by the QuAD algorithm to calculate each node’s overall strength . • • Base scores and strengths are in [0,1]. • Strength is a form of gradual acceptance [Cayrol and Lagasquie-Schiex, 2005] . • Firstly, a_acking and suppor'ng components (v a and v s ) are calculated for each node. Discon'nuity-Free Decision Support with Quan'ta've Argumenta'on Debates 4 / 24 A. Rago, F. Toni, M. Aurisicchio & P. Baroni

Background – QuAD Algorithm/Seman'cs Base scores are used by the QuAD algorithm to calculate each node’s overall strength . • • Base scores and strengths are in [0,1]. • Strength is a form of gradual acceptance [Cayrol and Lagasquie-Schiex, 2005] . • Firstly, a_acking and suppor'ng components (v a and v s ) are calculated for each node. Discon'nuity-Free Decision Support with Quan'ta've Argumenta'on Debates 4 / 24 A. Rago, F. Toni, M. Aurisicchio & P. Baroni

Background – QuAD Algorithm/Seman'cs Base scores are used by the QuAD algorithm to calculate each node’s overall strength . • • Base scores and strengths are in [0,1]. • Strength is a form of gradual acceptance [Cayrol and Lagasquie-Schiex, 2005] . • Firstly, a_acking and suppor'ng components (v a and v s ) are calculated for each node. Discon'nuity-Free Decision Support with Quan'ta've Argumenta'on Debates 4 / 24 A. Rago, F. Toni, M. Aurisicchio & P. Baroni

Background – QuAD Algorithm/Seman'cs Recursive formulae are used for a_acking and suppor'ng components. • 0 1 Discon'nuity-Free Decision Support with Quan'ta've Argumenta'on Debates 5 / 24 A. Rago, F. Toni, M. Aurisicchio & P. Baroni

Background – QuAD Algorithm/Seman'cs Recursive formulae are used for a_acking and suppor'ng components. • 0 1 Discon'nuity-Free Decision Support with Quan'ta've Argumenta'on Debates 5 / 24 A. Rago, F. Toni, M. Aurisicchio & P. Baroni

Background – QuAD Algorithm/Seman'cs Recursive formulae are used for a_acking and suppor'ng components. • 0 1 Discon'nuity-Free Decision Support with Quan'ta've Argumenta'on Debates 5 / 24 A. Rago, F. Toni, M. Aurisicchio & P. Baroni

Background – QuAD Algorithm/Seman'cs Recursive formulae are used for a_acking and suppor'ng components. • 0 1 • If the set of a_acker/supporter strengths is {} or a set of zeros it is considered ineffec0ve . Discon'nuity-Free Decision Support with Quan'ta've Argumenta'on Debates 5 / 24 A. Rago, F. Toni, M. Aurisicchio & P. Baroni

Background – QuAD Algorithm/Seman'cs Recursive formulae are used for a_acking and suppor'ng components. • 0 1 • If the set of a_acker/supporter strengths is {} or a set of zeros it is considered ineffec0ve . • The aggrega'ng func'on then determines the strength in the [0,1] range: v a v s Strength Effec've Ineffec've v a Ineffec've Effec've v s Ineffec've Ineffec've v 0 Effec've Effec've (v a + v s ) / 2 Discon'nuity-Free Decision Support with Quan'ta've Argumenta'on Debates 5 / 24 A. Rago, F. Toni, M. Aurisicchio & P. Baroni

Research Summary – Mo'va'on for DF-QuAD Engineering Design selng: • Issue – Which is the best method for controlling the ven'la'on of a dining room? – Answer 1 – Building management control – Answer 2 – User control – Discon'nuity-Free Decision Support with Quan'ta've Argumenta'on Debates 6 / 24 A. Rago, F. Toni, M. Aurisicchio & P. Baroni

Research Summary – Mo'va'on for DF-QuAD Engineering Design selng: • Issue – Which is the best method for controlling the ven'la'on of a dining room? – Answer 1 – Building management control – Answer 2 – User control – • Pro arguments are added at Stage 1 : Pro 1 – Energy is saved – Pro 2 – Elderly occupants require more simple selngs – Pro 3 – User sa'sfac'on is increased – Discon'nuity-Free Decision Support with Quan'ta've Argumenta'on Debates 6 / 24 A. Rago, F. Toni, M. Aurisicchio & P. Baroni

Research Summary – Mo'va'on for DF-QuAD Engineering Design selng: • Issue – Which is the best method for controlling the ven'la'on of a dining room? – Answer 1 – Building management control – Answer 2 – User control – • Pro arguments are added at Stage 1 : Pro 1 – Energy is saved – Pro 2 – Elderly occupants require more simple selngs – Pro 3 – User sa'sfac'on is increased – QuAD Algorithm: • Answer Strength at Stage 1 A1 0.925 A2 0.950 Discon'nuity-Free Decision Support with Quan'ta've Argumenta'on Debates 6 / 24 A. Rago, F. Toni, M. Aurisicchio & P. Baroni

Research Summary – Mo'va'on for DF-QuAD At Stage 2 , a con argument a_acking A2 is then added: • Con 1 – User negligence can lead to losses – Discon'nuity-Free Decision Support with Quan'ta've Argumenta'on Debates 7 / 24 A. Rago, F. Toni, M. Aurisicchio & P. Baroni

Research Summary – Mo'va'on for DF-QuAD At Stage 2 , a con argument a_acking A2 is then added: • Con 1 – User negligence can lead to losses – • QuAD Algorithm: Answer Strength at Strength Stage 1 at Stage 2 A1 0.925 0.925 A2 0.950 0.675 Discon'nuity-Free Decision Support with Quan'ta've Argumenta'on Debates 7 / 24 A. Rago, F. Toni, M. Aurisicchio & P. Baroni

Research Summary – Mo'va'on for DF-QuAD At Stage 2 , a con argument a_acking A2 is then added: • Con 1 – User negligence can lead to losses – • QuAD Algorithm: Answer Strength at Strength Stage 1 at Stage 2 A1 0.925 0.925 A2 0.950 0.675 • Large drop in A2’s strength between Stage 1 and 2 is dispropor'onate in some selngs, e.g. Engineering Design. • In other selngs, e.g. E-Democracy, this may not be the case. Discon'nuity-Free Decision Support with Quan'ta've Argumenta'on Debates 7 / 24 A. Rago, F. Toni, M. Aurisicchio & P. Baroni

Research Summary – Mo'va'on for DF-QuAD The aggrega'ng func'on’s range in one case is a subset of [0,1]: • v a and v s effec've otherwise Discon'nuity-Free Decision Support with Quan'ta've Argumenta'on Debates 8 / 24 A. Rago, F. Toni, M. Aurisicchio & P. Baroni

Research Summary – Mo'va'on for DF-QuAD The aggrega'ng func'on’s range in one case is a subset of [0,1]: • v a and v s effec've otherwise Strength of A2 at Stage 1 Discon'nuity-Free Decision Support with Quan'ta've Argumenta'on Debates 8 / 24 A. Rago, F. Toni, M. Aurisicchio & P. Baroni

Research Summary – Mo'va'on for DF-QuAD The aggrega'ng func'on’s range in one case is a subset of [0,1]: • v a and v s effec've otherwise Strength Strength of A2 at of A2 at Stage 2 Stage 1 • Discon'nuity, leading to counter-intui've behaviour in some applica'ons. Discon'nuity-Free Decision Support with Quan'ta've Argumenta'on Debates 8 / 24 A. Rago, F. Toni, M. Aurisicchio & P. Baroni

Research Summary – DF-QuAD Algorithm A new “discon'nuity-free” algorithm for QuAD frameworks (DF-QuAD). • • Incorporates many of the same concepts as the QuAD algorithm. – Base score and strength in [0,1]. Discon'nuity-Free Decision Support with Quan'ta've Argumenta'on Debates 9 / 24 A. Rago, F. Toni, M. Aurisicchio & P. Baroni